Knowledge

Odds ratio

Source 📝

25: 13438: 13374: 6296:, is very skewed. For example, if we are studying the relationship between high alcohol consumption and pancreatic cancer in the general population, the incidence of pancreatic cancer would be very low, so it would require a very large population sample to get a modest number of pancreatic cancer cases. However we could use data from hospitals to contact most or all of their pancreatic cancer patients, and then randomly sample an equal number of subjects without pancreatic cancer (this is called a "case-control study"). 6337: 13360: 4235: 3891: 13398: 6475:
members of a national disease foundation were actually 3.5 times more likely than nonmembers to have heard of a common treatment for that disease – but the odds ratio was 24 and the paper stated that members were ‘more than 20-fold more likely to have heard of’ the treatment. A study of papers published in two journals reported that 26% of the articles that used an odds ratio interpreted it as a risk ratio.
1836:. An odds ratio of 1 indicates that the condition or event under study is equally likely to occur in both groups. An odds ratio greater than 1 indicates that the condition or event is more likely to occur in the first group. And an odds ratio less than 1 indicates that the condition or event is less likely to occur in the first group. The odds ratio must be nonnegative if it is defined. It is undefined if 13386: 13426: 9278:
phone use in a control interval at the same time of day one week earlier. We would expect that a person's cell phone use at the time of the crash would be correlated with his/her use one week earlier. Comparing usage during the crash and control intervals adjusts for driver's characteristics and the time of day and day of the week. The data can be summarized in the following table.
6212: 2881: 2317: 5721: 465: 1428: 2603: 3163: 843: 4996: 5937: 6508:
not rare, thereby exaggerating differences when the OR rare-disease assumption is not met. On the other hand, when the disease is rare, using a RR for survival (e.g. the RR=0.9796 from above example) can clinically hide and conceal an important doubling of adverse risk associated with a drug or exposure.
4731: 9318:
There were 5 drivers who used their phones in both intervals, 27 who used them in the crash but not the control interval, 6 who used them in the control but not the crash interval, and 288 who did not use them in either interval. The odds ratio for crashing while using their phone relative to driving
7981:
Now concordant pairs in which either both the case and the control are exposed, or neither are exposed tell us nothing about the odds of exposure in cases relative to the odds of exposure among controls. The probability that the case is exposed and the control is not given that the pair is discordant
6507:
This is again what is called the 'invariance of the odds ratio', and why a RR for survival is not the same as a RR for risk, while the OR has this symmetrical property when analyzing either survival or adverse risk. The danger to clinical interpretation for the OR comes when the adverse event rate is
6503:
Suppose in a clinical trial, one has an adverse event risk of 4/100 in drug group, and 2/100 in placebo... yielding a RR=2 and OR=2.04166 for drug-vs-placebo adverse risk. However, if analysis was inverted and adverse events were instead analyzed as event-free survival, then the drug group would have
7310:
involves selecting representative samples of cases and controls who do, and do not, have some disease, respectively. These samples are usually independent of each other. The prior prevalence of exposure to some risk factor is observed in subjects from both samples. This permits the estimation of the
6356:
holds, the odds ratio is a good approximation to relative risk and that it has some advantages over relative risk. When the rare disease assumption does not hold, the unadjusted odds ratio will be greater than the relative risk, but novel methods can easily use the same data to estimate the relative
4238:
A graph showing the minimum value of the sample log odds ratio statistic that must be observed to be deemed significant at the 0.05 level, for a given sample size. The three lines correspond to different settings of the marginal probabilities in the 2×2 contingency table (the row and column marginal
6474:
Odds ratios have often been confused with relative risk in medical literature. For non-statisticians, the odds ratio is a difficult concept to comprehend, and it gives a more impressive figure for the effect. However, most authors consider that the relative risk is readily understood. In one study,
3441: 6499:
The odds ratio has another unique property of being directly mathematically invertible whether analyzing the OR as either disease survival or disease onset incidence – where the OR for survival is direct reciprocal of 1/OR for risk. This is known as the 'invariance of the odds ratio'. In contrast,
9277:
McEvoy et al. studied the use of cell phones by drivers as a risk factor for automobile crashes in a case-crossover study. All study subjects were involved in an automobile crash requiring hospital attendance. Each driver's cell phone use at the time of her/his crash was compared to her/his cell
1543:
It is standard in the medical literature to calculate the odds ratio and then use the rare-disease assumption (which is usually reasonable) to claim that the relative risk is approximately equal to it. This not only allows for the use of case-control studies, but makes controlling for confounding
6490:
While relative risks are potentially easier to interpret for a general audience, there are mathematical and conceptual advantages when using an odds-ratio instead of a relative risk, particularly in regression models. For that reason, there is not a consensus within the fields of epidemiology or
164:
If we flip an unbiased coin, the probability of getting heads and the probability of getting tails are equal — both are 50%. Imagine we get a biased coin that makes it two times more likely to get heads. But what does "twice as likely" mean in terms of a probability? It cannot literally mean to
2650: 2086: 6504:
a rate of 96/100, and placebo group would have a rate of 98/100—yielding a drug-vs-placebo a RR=0.9796 for survival, but an OR=0.48979. As one can see, a RR of 0.9796 is clearly not the reciprocal of a RR of 2. In contrast, an OR of 0.48979 is indeed the direct reciprocal of an OR of 2.04166.
6458:
Consider the death rate of men and women passengers when a ship sank. Of 462 women, 154 died and 308 survived. Of 851 men, 709 died and 142 survived. Clearly a man on the ship was more likely to die than a woman, but how much more likely? Since over half the passengers died, the rare disease
6567:
A number of alternative estimators of the odds ratio have been proposed to address limitations of the sample odds ratio. One alternative estimator is the conditional maximum likelihood estimator, which conditions on the row and column margins when forming the likelihood to maximize (as in
109:
if and only if the OR equals 1, i.e., the odds of one event are the same in either the presence or absence of the other event. If the OR is greater than 1, then A and B are associated (correlated) in the sense that, compared to the absence of B, the presence of B raises the odds of A, and
132:(ARR). Often, the parameter of greatest interest is actually the RR, which is the ratio of the probabilities analogous to the odds used in the OR. However, available data frequently do not allow for the computation of the RR or the ARR, but do allow for the computation of the OR, as in 1815: 4440: 7579:. We consider each pair as belonging to a stratum with identical values of the confounding variables. Conditioned on belonging to the same stratum, the exposure status of cases and controls are independent of each other. For any case-control pair within the same stratum let 4103:
Alternatively, the odds of a man drinking wine are 90 to 10, or 9:1, while the odds of a woman drinking wine are only 20 to 60, or 1:3 = 0.33. The odds ratio is thus 9/0.33, or 27, showing that men are much more likely to drink wine than women. The detailed calculation is:
1131: 4209:
This example also shows how odds ratios are sometimes sensitive in stating relative positions: in this sample men are (90/100)/(20/80) = 3.6 times as likely to have drunk wine than women, but have 27 times the odds. The logarithm of the odds ratio, the difference of the
5395: 4569: 2008: 5216: 6478:
This may reflect the simple process of uncomprehending authors choosing the most impressive-looking and publishable figure. But its use may in some cases be deliberately deceptive. It has been suggested that the odds ratio should only be presented as a measure of
394: 9260: 1357: 6438: 4028: 4204: 2328: 2892: 610: 6252:. This shows that the odds ratio (and consequently the log odds ratio) is invariant to non-random sampling based on one of the variables being studied. Note however that the standard error of the log odds ratio does depend on the value of 3836: 6207:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&{\frac {fp_{11}}{p_{11}+p_{10}}}&{\frac {fp_{10}}{p_{11}+p_{10}}}\\X=0&{\frac {(1-f)p_{01}}{p_{01}+p_{00}}}&{\frac {(1-f)p_{00}}{p_{01}+p_{00}}}\end{array}}} 4809: 4580: 8342: 3238: 9640: 6550:
is easy to calculate, and for moderate and large samples performs well as an estimator of the population odds ratio. When one or more of the cells in the contingency table can have a small value, the sample odds ratio can be
2876:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&{\frac {p_{11}}{p_{11}+p_{01}}}&{\frac {p_{10}}{p_{10}+p_{00}}}\\X=0&{\frac {p_{01}}{p_{11}+p_{01}}}&{\frac {p_{00}}{p_{10}+p_{00}}}\end{array}}} 2312:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&{\frac {p_{11}}{p_{11}+p_{10}}}&{\frac {p_{10}}{p_{11}+p_{10}}}\\X=0&{\frac {p_{01}}{p_{01}+p_{00}}}&{\frac {p_{00}}{p_{01}+p_{00}}}\end{array}}} 6500:
the relative risk does not possess this mathematical invertible property when studying disease survival vs. onset incidence. This phenomenon of OR invertibility vs. RR non-invertibility is best illustrated with an example:
1564:
of an event occurring in one group to the odds of it occurring in another group. The term is also used to refer to sample-based estimates of this ratio. These groups might be men and women, an experimental group and a
3637: 8111: 7954: 5085: 1347:. One could take a random sample of fifty villagers, but quite possibly such a random sample would not include anybody with the disease, since only 2.6% of the population are diseased. Instead, one might use a 6462:
To compute the odds ratio, note that for women the odds of dying were 1 to 2 (154/308). For men, the odds were 5 to 1 (709/142). The odds ratio is 9.99 (4.99/.5). Men had ten times the odds of dying as women.
4098: 110:
symmetrically the presence of A raises the odds of B. Conversely, if the OR is less than 1, then A and B are negatively correlated, and the presence of one event reduces the odds of the other event occurring.
3934:
Suppose that in a sample of 100 men, 90 drank wine in the previous week (so 10 did not), while in a sample of 80 women only 20 drank wine in the same period (so 60 did not). This forms the contingency table:
1593: 8804:
by showing that it is a special case of the Mantel-Haenszel estimate of the intra-strata odds ratio for stratified 2x2 tables. They also reference Breslow & Day as providing the derivation given here.
4256: 8539: 997: 5716:{\displaystyle e^{\beta _{x}}=\exp(\beta _{x})={\frac {P(Y=1\mid X=1,Z_{1},\ldots ,Z_{p})/P(Y=0\mid X=1,Z_{1},\ldots ,Z_{p})}{P(Y=1\mid X=0,Z_{1},\ldots ,Z_{p})/P(Y=0\mid X=0,Z_{1},\ldots ,Z_{p})}},} 1351:
in which all 26 diseased villagers are interviewed as well as a random sample of 26 who do not have the disease. The results might turn out as follows ("might", because this is a random sample):
6466:
For women, the probability of death was 33% (154/462). For men the probability was 83% (709/851). The relative risk of death is 2.5 (.83/.33). A man had 2.5 times a woman's probability of dying.
4454: 1893: 1540:
to figure those out. Because the study selected for people with the disease, half the people in the sample have the disease and it is known that that is more than the population-wide prevalence.
1486:, quite close to the odds ratio calculated for the entire village. The relative risk, however, cannot be calculated, because it is the ratio of the risks of getting the disease and we would need 3446:
In this case, the odds ratio equals one, and conversely the odds ratio can only equal one if the joint probabilities can be factored in this way. Thus the odds ratio equals one if and only if
460:{\displaystyle {\begin{array}{|r|cc|}\hline &{\text{ Diseased }}&{\text{ Healthy }}\\\hline {\text{ Exposed }}&20&380\\{\text{ Not exposed }}&6&594\\\hline \end{array}}} 8414: 5100: 985: 1484: 1423:{\displaystyle {\begin{array}{|r|cc|}\hline &{\text{ Diseased }}&{\text{ Healthy }}\\\hline {\text{ Exposed }}&20&10\\{\text{ Not exposed }}&6&16\\\hline \end{array}}} 915: 9127: 8598: 6366: 5820: 5772: 8870: 10309:
Commentary on controversy and debate 4 paper series: Questionable utility of the relative risk in clinical research. (2022/02//). Journal of Clinical Epidemiology, 142, 268-270. doi:
9368: 2632:. However in some applications the labeling of categories as zero and one is arbitrary, so there is nothing special about concordant versus discordant values in these applications. 534: 5892: 596: 8453: 8196: 3941: 2598:{\displaystyle OR={\dfrac {p_{11}/(p_{11}+p_{10})}{p_{10}/(p_{11}+p_{10})}}{\bigg /}{\dfrac {p_{01}/(p_{01}+p_{00})}{p_{00}/(p_{01}+p_{00})}}={\frac {p_{11}p_{00}}{p_{10}p_{01}}}} 9100: 6300:
In both these settings, the odds ratio can be calculated from the selected sample, without biasing the results relative to what would have been obtained for a population sample.
5383: 3158:{\displaystyle {\dfrac {p_{11}/(p_{11}+p_{01})}{p_{01}/(p_{11}+p_{01})}}{\bigg /}{\dfrac {p_{10}/(p_{10}+p_{00})}{p_{00}/(p_{10}+p_{00})}}={\dfrac {p_{11}p_{00}}{p_{10}p_{01}}}.} 9034: 8995: 4110: 3466:
The odds ratio is a function of the cell probabilities, and conversely, the cell probabilities can be recovered given knowledge of the odds ratio and the marginal probabilities
1222: 1182: 9441: 10183:
Nijsten T, Rolstad T, Feldman SR, Stern RS (January 2005). "Members of the national psoriasis foundation: more extensive disease and better informed about treatment options".
9406: 9477: 1277: 8802: 8769: 8736: 1248: 8707: 8630: 7731: 7683: 6352:
is usually better than the odds ratio for understanding the relation between risk and some variable such as radiation or a new drug. That section also explains that if the
838:{\displaystyle {\text{Relative risk}}={\frac {D_{E}/(D_{E}+H_{E})}{D_{N}/(D_{N}+H_{N})}}={\frac {D_{E}/V_{E}}{D_{N}/V_{N}}}={\frac {20/400}{6/600}}={\frac {.05}{.01}}=5\,.} 7808: 7771: 316: 214: 382: 280: 9762: 8925: 4991:{\displaystyle {L=\log \left({\dfrac {{\hat {p}}_{11}{\hat {p}}_{00}}{{\hat {p}}_{10}{\hat {p}}_{01}}}\right)=\log \left({\dfrac {n_{11}n_{00}}{n_{10}n_{01}}}\right)}} 3692: 247: 9507: 8899: 7568:
pairs were neither subject was exposed. The exposure of matched case and control pairs is correlated due to the similar values of their shared confounding variables.
349: 8140: 7566: 7539: 7512: 7485: 7453: 7425: 7392: 7364: 1433:
The odds in this sample of getting the disease given that someone is exposed is 20/10 and the odds given that someone is not exposed is 6/16. The odds ratio is thus
9558: 9120: 8674: 7976: 7635: 7606: 7315:
variables. In this case, the prior exposure of interest is determined for each case and her/his matched control. The data can be summarized in the following table.
1538: 1511: 1345: 1318: 9538: 9054: 8956: 8654: 8220: 4726:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&{\hat {p}}_{11}&{\hat {p}}_{10}\\X=0&{\hat {p}}_{01}&{\hat {p}}_{00}\end{array}}} 6455:
If the rare disease assumption does not apply, the odds ratio may be very different from the relative risk and should not be interpreted as a relative risk.
3436:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&p_{x}p_{y}&p_{x}(1-p_{y})\\X=0&(1-p_{x})p_{y}&(1-p_{x})(1-p_{y})\end{array}}} 9974:
Robbins AS, Chao SY, Fonseca VP (October 2002). "What's the relative risk? A method to directly estimate risk ratios in cohort studies of common outcomes".
8227: 180:
Suppose a radiation leak in a village of 1,000 people increased the incidence of a rare disease. The total number of people exposed to the radiation was
6487:
cannot be estimated directly, but with newly available methods it is always possible to estimate the risk ratio, which should generally be used instead.
9565: 13473: 10579: 7273: 7267: 105:, odds ratio reciprocally calculates the ratio of the odds of B occurring in the presence of A, and the odds of B in the absence of A. Two events are 7311:
odds ratio for disease in exposed vs. unexposed people as noted above. Sometimes, however, it makes sense to match cases to controls on one or more
1362: 399: 5249:
to obtain a 95% confidence interval for the odds ratio. If we wish to test the hypothesis that the population odds ratio equals one, the two-sided
6491:
biostatistics that relative risks or odds-ratios should be preferred when both can be validly used, such as in clinical trials and cohort studies
9269:. This technique has the advantage of allowing users to regress case-control status against multiple risk factors from matched case-control data. 1285:
is easier to understand than the odds ratio, but one reason to use odds ratio is that usually, data on the entire population is not available and
3524: 1544:
variables such as weight or age using regression analysis easier and has the desirable properties discussed in other sections of this article of
12495: 7987: 7815: 5902:
values. In many settings it is impractical to obtain a population sample, so a selected sample is used. For example, we may choose to sample
1289:
must be used. In the example above, if it were very costly to interview villagers and find out if they were exposed to the radiation, then the
13000: 7290:; these two are normalized so they are 0 for independent events, 1 for perfectly correlated, −1 for perfectly negatively correlated. 1810:{\displaystyle OR={\frac {p_{1}/(1-p_{1})}{p_{2}/(1-p_{2})}}={\frac {p_{1}/q_{1}}{p_{2}/q_{2}}}={\frac {\;p_{1}q_{2}\;}{\;p_{2}q_{1}\;}},} 13150: 5012: 9931:
Zhang J, Yu KF (November 1998). "What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes".
5942: 5286:
An alternative approach to inference for odds ratios looks at the distribution of the data conditionally on the marginal frequencies of
4585: 4459: 4039: 3946: 3243: 2655: 2091: 1898: 12774: 11415: 6573: 4435:{\displaystyle {\log \left({\frac {p_{11}p_{00}}{p_{01}p_{10}}}\right)=\log(p_{11})+\log(p_{00}{\big )}-\log(p_{10})-\log(p_{01})}.\,} 9768: 136:, as explained below. On the other hand, if one of the properties (A or B) is sufficiently rare (in epidemiology this is called the 12548: 10871: 10867: 7198: 6328:. It is often abbreviated "OR" in reports. When data from multiple surveys is combined, it will often be expressed as "pooled OR". 1126:{\displaystyle {\text{Odds ratio}}={\frac {D_{E}/H_{E}}{D_{N}/H_{N}}}={\frac {20/380}{6/594}}\approx {\frac {.0526}{.0101}}=5.2\,.} 12987: 10917: 10875: 10863: 9513: 8935: 8460: 10572: 9483:
value of 0.0003. This allows us to reject the hypothesis that cell phone use has no effect on the risk of automobile crashes (
10331: 7294:
studied these and argued that these measures of association must be functions of the odds ratio, which he referred to as the
4564:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&n_{11}&n_{10}\\X=0&n_{01}&n_{00}\end{array}}} 2608:
The simple expression on the right, above, is easy to remember as the product of the probabilities of the "concordant cells"
2003:{\displaystyle {\begin{array}{c|cc}&Y=1&Y=0\\\hline X=1&p_{11}&p_{10}\\X=0&p_{01}&p_{00}\end{array}}} 9772: 11410: 11110: 11038: 10954: 6312:, the odds ratio is widely used in many fields of medical and social science research. The odds ratio is commonly used in 118: 10117: 5211:{\displaystyle {{\rm {SE}}={\sqrt {{\dfrac {1}{n_{11}}}+{\dfrac {1}{n_{10}}}+{\dfrac {1}{n_{01}}}+{\dfrac {1}{n_{00}}}}}}} 12014: 11162: 10819: 5222:
This is an asymptotic approximation, and will not give a meaningful result if any of the cell counts are very small. If
10789: 9255:{\displaystyle ({\frac {{\hat {\pi }}_{LB}}{1-{\hat {\pi }}_{LB}}},{\frac {{\hat {\pi }}_{UB}}{1-{\hat {\pi }}_{UB}}})} 8349: 924: 1436: 855: 12797: 12689: 10565: 106: 68: 46: 6584:
The following four contingency tables contain observed cell counts, along with the corresponding sample odds ratio (
6433:{\displaystyle {\text{Relative risk}}\approx {\frac {\text{Odds ratio}}{1-R_{C}+(R_{C}\times {\text{Odds ratio}})}}} 39: 13402: 12975: 12849: 11076: 10547: 8772: 4246:
One approach to inference uses large sample approximations to the sampling distribution of the log odds ratio (the
8546: 169:
that are doubling: from 1:1 odds, to 2:1 odds. The new probabilities would be 66⅔% for heads and 33⅓% for tails.
13033: 12694: 12439: 11810: 11400: 10542: 9645: 9266: 5305:
is one way to generalize the odds ratio beyond two binary variables. Suppose we have a binary response variable
5280: 10883: 13084: 12296: 12103: 11992: 11950: 10921: 10643: 6758: 5777: 5729: 5294:. An advantage of this approach is that the sampling distribution of the odds ratio can be expressed exactly. 12024: 8811: 4250:
of the odds ratio). If we use the joint probability notation defined above, the population log odds ratio is
13327: 12286: 11189: 11069: 10754: 9324: 8739: 8199: 4023:{\displaystyle {\begin{array}{c|cc}&M=1&M=0\\\hline D=1&90&20\\D=0&10&60\end{array}}} 477: 13468: 12878: 12827: 12812: 12802: 12671: 12543: 12510: 12336: 12291: 12121: 11048: 5855: 4199:{\displaystyle {0.9/0.1 \over 0.2/0.6}={\frac {\;0.9\times 0.6\;}{\;0.1\times 0.2\;}}={0.54 \over 0.02}=27} 539: 9443:
given 27 out of 33 discordant pairs in which the driver was using her/his phone at the time of his crash.
8419: 8149: 13463: 13390: 13222: 13023: 12947: 12248: 12002: 11671: 11135: 11012: 10984: 10913: 10667: 10449:"Role of mobile phones in motor vehicle crashes resulting in hospital attendance: a case-crossover study" 9059: 6263:
Suppose it is inconvenient or impractical to obtain a population sample, but it is practical to obtain a
5352: 5091: 9648:
and obtained almost identical results to those given here. See the last row of Table 3 in their paper.)
9000: 8961: 1187: 1147: 13416: 13107: 13079: 13074: 12822: 12581: 12487: 12467: 12375: 12086: 11904: 11387: 11259: 11062: 10738: 10056: 9411: 6360:
If the absolute risk in the unexposed group is available, conversion between the two is calculated by:
9376: 12839: 12607: 12328: 12253: 12182: 12111: 12031: 12019: 11889: 11877: 11870: 11578: 11299: 10857: 9846:"Calculating confidence intervals for relative risks (odds ratios) and standardised ratios and rates" 9449: 6289:
values are representative of the population (i.e. they follow the correct conditional probabilities).
3192:
are independent, their joint probabilities can be expressed in terms of their marginal probabilities
2054: 1253: 9893:
Viera AJ (July 2008). "Odds ratios and risk ratios: what's the difference and why does it matter?".
8778: 8745: 8712: 5894:
are interpreted as the frequencies of each of the four groups in the population as defined by their
1227: 13322: 13089: 12952: 12637: 12602: 12566: 12351: 11793: 11702: 11661: 11573: 11264: 11103: 10795: 10743: 10623: 8683: 8606: 7690: 7642: 3461: 3455: 1872: 94: 33: 13231: 12844: 12784: 12721: 12359: 12343: 12081: 11943: 11933: 11783: 11697: 10841: 10711: 10689: 10658: 10633: 10616: 10552: 7576: 7167: 7098: 7042: 6353: 3831:{\displaystyle S={\sqrt {(1+(p_{1\cdot }+p_{\cdot 1})(R-1))^{2}+4R(1-R)p_{1\cdot }p_{\cdot 1}}}.} 1137: 174: 165:
double the original probability value, because doubling 50% would yield 100%. Rather, it is the
137: 129: 7776: 7739: 285: 183: 13269: 13199: 12992: 12929: 12684: 12571: 11568: 11465: 11372: 11251: 11150: 10992: 10829: 10750: 7120: 6761:
contain the population cell probabilities, along with the corresponding population odds ratio (
6569: 5917:, regardless of their frequency in the population (which would necessitate sampling units with 2996: 2441: 354: 252: 50: 8904: 3894:
A graph showing how the log odds ratio relates to the underlying probabilities of the outcome
3882:, the other three cell probabilities can easily be recovered from the marginal probabilities. 219: 13458: 13294: 13236: 13179: 13005: 12898: 12807: 12533: 12417: 12276: 12268: 12158: 12150: 11965: 11861: 11839: 11798: 11763: 11730: 11676: 11651: 11606: 11545: 11505: 11307: 11130: 10833: 10720: 10628: 10592: 10447:
McEvoy SP, Stevenson MR, McCartt AT, Woodward M, Haworth C, Palamara P, Cercarelli R (2005).
9667: 9486: 8878: 8633: 8143: 321: 10557: 10553:
OpenEpi, a web-based program that calculates the odds ratio, both unmatched and pair-matched
10009:
Nurminen M (August 1995). "To use or not to use the odds ratio in epidemiologic analyses?".
8118: 7544: 7517: 7490: 7463: 7431: 7403: 7370: 7342: 101:
of event A taking place in the presence of B, and the odds of A in the absence of B. Due to
13217: 12792: 12741: 12717: 12679: 12597: 12576: 12528: 12407: 12385: 12354: 12263: 12140: 12091: 12009: 11982: 11938: 11894: 11656: 11432: 11312: 10799: 9543: 9105: 8659: 7961: 7613: 7584: 6325: 1516: 1489: 1323: 1296: 9523: 9039: 8941: 8639: 8205: 8: 13364: 13289: 13212: 12893: 12657: 12650: 12612: 12520: 12500: 12472: 12205: 12071: 12066: 12056: 12048: 11866: 11827: 11717: 11707: 11616: 11395: 11351: 11269: 11194: 11096: 10706: 10638: 9517: 6309: 6264: 5302: 5227: 5003: 148: 6345: 13442: 13378: 13189: 13043: 12939: 12888: 12764: 12661: 12645: 12622: 12399: 12133: 12116: 12076: 11987: 11882: 11844: 11815: 11775: 11735: 11681: 11598: 11284: 11279: 10959: 10909: 10724: 10653: 10611: 10523: 10475: 10448: 10422: 10287: 10262: 10243: 10160: 10135: 10095: 10034: 9956: 9870: 9845: 9826: 9813: 9796: 9738: 9713: 8677: 7307: 7058: 6951: 4223: 1348: 133: 10231: 9987: 8337:{\displaystyle {\hat {\pi }}=n_{10}/(n_{10}+n_{01})={\hat {\psi }}/({\hat {\psi }}+1)} 3906:. The log odds ratio shown here is based on the odds for the event occurring in group 172: 13437: 13373: 13284: 13254: 13246: 13066: 13057: 12982: 12913: 12769: 12754: 12729: 12617: 12558: 12424: 12412: 12038: 11955: 11899: 11822: 11666: 11588: 11367: 11241: 11033: 10997: 10964: 10889: 10811: 10588: 10480: 10426: 10374:
Statistical Methods in Cancer Research: Vol. 1 - The Analysis of Case-Control Studies
10327: 10292: 10235: 10200: 10165: 10087: 10079: 10026: 9991: 9948: 9910: 9875: 9818: 9743: 9725: 9444: 8928: 6552: 5903: 4446: 4247: 385: 10247: 10099: 10038: 9960: 13309: 13264: 13028: 13015: 12908: 12883: 12817: 12749: 12627: 12235: 12128: 12061: 11974: 11921: 11740: 11611: 11405: 11289: 11204: 11171: 10807: 10728: 10682: 10677: 10515: 10503: 10470: 10460: 10418: 10282: 10274: 10227: 10192: 10155: 10147: 10071: 10018: 9983: 9940: 9902: 9865: 9857: 9830: 9808: 9733: 9682: 9635:{\displaystyle ({\frac {0.6561}{1-0.6561}},{\frac {0.9139}{1-0.9139}})=(1.9,10.6)} 5327:
that may or may not be binary. If we use multiple logistic regression to regress
1224:. Thus, the denominators in the relative risk and odds ratio are almost the same ( 13430: 13226: 12970: 12832: 12759: 12434: 12308: 12281: 12258: 12227: 11854: 11849: 11803: 11533: 11184: 11002: 10825: 10780: 10310: 10057:"Estimating risk and rate levels, ratios and differences in case-control studies" 9906: 7460:
This table gives the exposure status of the matched pairs of subjects. There are
6313: 4243:
Several approaches to statistical inference for odds ratios have been developed.
4226:, an odds ratio of 27/1 maps to 3.296, and an odds ratio of 1/27 maps to −3.296. 2640:
If we had calculated the odds ratio based on the conditional probabilities given
1876: 1286: 1144:
and the odds ratio are almost the same. By definition, rare disease implies that
12716: 10465: 10407:"Estimation of multiple relative risk functions in matched case-control studies" 5931:). In this situation, our data would follow the following joint probabilities: 3462:
Recovering the cell probabilities from the odds ratio and marginal probabilities
121:): an OR greater than 1 does not establish that B causes A, or that A causes B. 13175: 13170: 11633: 11563: 11209: 11028: 10949: 10901: 10694: 10606: 7572: 6321: 5389:
is related to a conditional odds ratio. Specifically, at the population level
10218:
Holcomb W (2001). "An odd measure of risk: Use and misuse of the odds ratio".
10196: 9861: 7810:. The within-stratum odds ratio for exposure in cases relative to controls is 7541:
pairs where the control subject was exposed but the case patient was not, and
13452: 13332: 13299: 13162: 13123: 12934: 12903: 12367: 12321: 11926: 11628: 11455: 11219: 11214: 11007: 10974: 10969: 10278: 10083: 9944: 9729: 7144: 6349: 3930:, the odds ratio is greater than 1, and the log odds ratio is greater than 0. 3173: 1866: 1573:
classification. If the probabilities of the event in each of the groups are
1566: 1282: 1141: 600: 125: 124:
Two similar statistics that are often used to quantify associations are the
13274: 13207: 13184: 13099: 12429: 11725: 11623: 11558: 11500: 11485: 11422: 11377: 10849: 10733: 10484: 10239: 10204: 10169: 10091: 9995: 9914: 9822: 9747: 9677: 9657: 7085: 6336: 6317: 3632:{\displaystyle p_{11}={\frac {1+(p_{1\cdot }+p_{\cdot 1})(R-1)-S}{2(R-1)}}} 598:. One obvious way to compare the risks is to use the ratio of the two, the 97:
between two events, A and B. The odds ratio is defined as the ratio of the
10296: 10151: 10030: 9952: 9879: 7514:
pairs where the case patient was exposed but the control subject was not,
1293:
of radiation exposure would not be known, and neither would the values of
13317: 13279: 12962: 12863: 12725: 12538: 12505: 11997: 11914: 11909: 11553: 11510: 11490: 11470: 11460: 11229: 11043: 10897: 10770: 10760: 10430: 10406: 9672: 9662: 8106:{\displaystyle \pi =(p_{1}q_{0})/(p_{1}q_{0}+q_{1}p_{0})=\psi /(\psi +1)} 7949:{\displaystyle \psi =(p_{1}/q_{1})/(p_{0}/q_{0})=p_{1}q_{0}/(q_{1}p_{0})} 7312: 7295: 7284: 7277: 6480: 4215: 3169: 12163: 11643: 11343: 11274: 11224: 11199: 11119: 10837: 10803: 10765: 10672: 10527: 10394:. Philadelphia, PA: Lippincott Williams & Wilkins. p. 287,288. 10022: 9687: 6484: 1290: 2620:
divided by the product of the probabilities of the "discordant cells"
12316: 12168: 11788: 11583: 11495: 11480: 11475: 11440: 10905: 10893: 10075: 7773:, and the probability that a control is exposed and a case in not is 5774:
is an estimate of this conditional odds ratio. The interpretation of
4803:
being the sum of all four cell counts. The sample log odds ratio is
4574:
then the probabilities in the joint distribution can be estimated as
2041:
are non-negative "cell probabilities" that sum to one. The odds for
1570: 90: 10519: 7736:
Then the probability that a case is exposed and a control is not is
7487:
pairs where both the case and her/his matched control were exposed,
5852:
If the data form a "population sample", then the cell probabilities
4234: 11832: 11450: 11327: 11322: 11317: 10939: 6556: 5080:{\displaystyle L\ \sim \ {\mathcal {N}}(\log(OR),\,\sigma ^{2}).\,} 4219: 4033:
The odds ratio (OR) can be directly calculated from this table as:
9718:
Journal of the Canadian Academy of Child and Adolescent Psychiatry
4093:{\displaystyle {OR}={\frac {\;90\times 60\;}{\;10\times 20\;}}=27} 13337: 13038: 10944: 10136:"Against all odds? Improving the understanding of risk reporting" 6357:
risk, risk differences, base probabilities, or other quantities.
5250: 3890: 113:
Note that the odds ratio is symmetric in the two events, and no
13259: 12240: 12214: 12194: 11445: 11236: 10405:
Breslow NE, Day NE, Halvorsen KT, Prentice RL, Sabai C (1978).
6771: 6594: 140:), then the OR is approximately equal to the corresponding RR. 114: 10446: 10376:. Lyon, France: IARC Scientific Publications. p. 162-189. 9036:
denote the lower and upper bound of a confidence interval for
7301: 11088: 10587: 4211: 282:
stayed healthy. The total number of people not exposed was
11179: 10404: 9540:
is (0.6561, 0.9139). Hence, a 95% confidence interval for
8534:{\displaystyle n_{10}={\hat {\psi }}(n_{10}+n_{01}-n_{10})} 7685:
be the probability that a case patient is not exposed, and
4222:
with respect to the ordering of groups. For example, using
1561: 98: 10182: 10133: 7733:
be the probability that a control patient is not exposed.
1867:
Definition in terms of joint and conditional probabilities
1549: 159: 1871:
The odds ratio can also be defined in terms of the joint
1555: 9479:. This statistic has one degree of freedom and yields a 5847: 5002:
The distribution of the log odds ratio is approximately
16:
Statistic quantifying the association between two events
10506:(1963). "The Measure of Association in a 2 × 2 Table". 6292:
Suppose the marginal distribution of one variable, say
3179: 10118:"On the use, misuse and interpretation of odds ratios" 7637:
be the probability that a control patient is exposed,
6248:
for this distribution does not depend on the value of
3910:
relative to the odds for the event occurring in group
13414: 9568: 9546: 9526: 9489: 9452: 9414: 9379: 9327: 9130: 9108: 9062: 9042: 9003: 8964: 8944: 8907: 8881: 8814: 8781: 8748: 8715: 8686: 8662: 8642: 8609: 8549: 8463: 8422: 8352: 8230: 8208: 8152: 8121: 7990: 7964: 7818: 7779: 7742: 7693: 7645: 7616: 7587: 7547: 7520: 7493: 7466: 7434: 7406: 7373: 7345: 7276:
that measure association between two events, such as
6369: 5940: 5858: 5780: 5732: 5398: 5355: 5187: 5165: 5143: 5121: 5103: 5015: 4934: 4831: 4812: 4583: 4457: 4259: 4113: 4042: 3944: 3695: 3527: 3241: 3103: 3002: 2897: 2895: 2653: 2447: 2342: 2331: 2089: 1896: 1879:. The joint distribution of binary random variables 1596: 1519: 1492: 1439: 1360: 1326: 1299: 1256: 1230: 1190: 1150: 1000: 927: 858: 613: 542: 480: 397: 357: 324: 288: 255: 222: 186: 13001:
Autoregressive conditional heteroskedasticity (ARCH)
10389: 10349: 10321: 9797:"Understanding the Odds Ratio and the Relative Risk" 6259:
This fact is exploited in two important situations:
5313:, and in addition we have other predictor variables 536:
and of developing the disease given non-exposure is
7608:be the probability that a case patient is exposed, 12463: 10548:Odds Ratio Calculator with various tests – website 9973: 9634: 9552: 9532: 9501: 9471: 9435: 9400: 9362: 9254: 9114: 9094: 9048: 9028: 8989: 8950: 8919: 8893: 8864: 8796: 8763: 8730: 8701: 8668: 8648: 8624: 8592: 8533: 8447: 8408: 8336: 8214: 8190: 8134: 8105: 7970: 7948: 7802: 7765: 7725: 7677: 7629: 7600: 7560: 7533: 7506: 7479: 7447: 7419: 7386: 7358: 7268:Category:Summary statistics for contingency tables 6432: 6206: 5886: 5814: 5766: 5715: 5377: 5210: 5079: 4990: 4725: 4563: 4434: 4218:, tempers this effect, and also makes the measure 4198: 4092: 4022: 3830: 3631: 3435: 3157: 2875: 2597: 2311: 2002: 1809: 1532: 1505: 1478: 1422: 1339: 1312: 1271: 1242: 1216: 1176: 1125: 979: 909: 837: 590: 528: 459: 376: 343: 310: 274: 241: 208: 154: 9509:) with a high level of statistical significance. 8409:{\displaystyle (n_{10}+n_{01})({\hat {\psi }}+1)} 5226:is the sample log odds ratio, an approximate 95% 1545: 980:{\displaystyle D_{N}/H_{N}=6/594\approx .0101\,.} 13450: 9408:is the same as testing the null hypothesis that 1479:{\displaystyle {\frac {20/10}{6/16}}\approx 5.3} 910:{\displaystyle D_{E}/H_{E}=20/380\approx .0526,} 144: 12549:Multivariate adaptive regression splines (MARS) 10134:A'Court C, Stevens R, Heneghan C (March 2012). 10115: 9850:British Medical Journal (Clinical Research Ed.) 9790: 9788: 6511: 6494: 6303: 10371: 10354:. Philadelphia, PA: Elsevier. p. 149-177. 10311:https://doi.org/10.1016/j.jclinepi.2021.09.016 9265:Matched 2x2 tables may also be analyzed using 5297: 11104: 10573: 9926: 9924: 9843: 6469: 6452:is the absolute risk of the unexposed group. 4372: 10263:"Social perception of the mentally retarded" 10116:Taeger D, Sun Y, Straif K (10 August 1998). 9785: 9754: 9102:, the corresponding confidence interval for 8875:Hence, we can test the null hypothesis that 8593:{\displaystyle {\hat {\psi }}=n_{10}/n_{01}} 6331: 5822:is as an estimate of the odds ratio between 474:of developing the disease given exposure is 173:A motivating example, in the context of the 10367: 10365: 10363: 10361: 9967: 9886: 8346:Multiplying both sides of this equation by 7302:Odds Ratio for a Matched Case-Control Study 11149: 11111: 11097: 10580: 10566: 10398: 10385: 10383: 10111: 10109: 9921: 9837: 8934:There are a number of ways to calculate a 4173: 4163: 4160: 4150: 4080: 4070: 4067: 4057: 1800: 1779: 1776: 1755: 384:stayed healthy. We can organize this in a 13474:Summary statistics for contingency tables 11762: 10474: 10464: 10442: 10440: 10390:Rothman KJ, Greenland S, Lash TL (2008). 10345: 10343: 10322:Rothman KJ, Greenland S, Lash TL (2008). 10286: 10159: 10129: 10127: 9869: 9812: 9769:Boston University School of Public Health 9737: 9644:(McEvoy et al. analyzed their data using 7274:summary statistics for contingency tables 6572:). Another alternative estimator is the 6562: 5867: 5815:{\displaystyle \exp({\hat {\beta }}_{x})} 5767:{\displaystyle \exp({\hat {\beta }}_{x})} 5076: 5059: 4431: 2045:within the two subpopulations defined by 1119: 973: 831: 69:Learn how and when to remove this message 10872:Preventable fraction among the unexposed 10868:Attributable fraction for the population 10508:Journal of the Royal Statistical Society 10358: 10350:Celentano DD, Szklo M, Gordis L (2019). 10054: 10008: 9711: 8865:{\displaystyle \psi =1,\pi =1/(1+1)=0.5} 8775:et al. give an alternate derivation of 8142:given the number of discordant pairs is 7199:Preventable fraction among the unexposed 6335: 5094:for the log odds ratio is approximately 4233: 4229: 3889: 1587:(second group), then the odds ratio is: 32:This article includes a list of general 10876:Preventable fraction for the population 10864:Attributable fraction among the exposed 10502: 10380: 10217: 10140:The British Journal of General Practice 10106: 9930: 9760: 9363:{\displaystyle {\hat {\psi }}=27/6=4.5} 7291: 4239:probabilities are equal in this graph). 2886:we would have obtained the same result 160:Intuition from an example for laypeople 13451: 13075:Kaplan–Meier estimator (product limit) 10437: 10340: 10260: 10124: 10050: 10048: 8771:given the number of discordant pairs. 1556:Definition in terms of group-wise odds 529:{\displaystyle D_{E}/V_{E}=20/400=.05} 13148: 12715: 12462: 11761: 11531: 11148: 11092: 10561: 10326:. Lippincott Williams & Wilkins. 9892: 9794: 7261: 6579: 6320:, and to express the results of some 5887:{\displaystyle {\widehat {p\,}}_{ij}} 5848:Insensitivity to the type of sampling 5230:for the population log odds ratio is 1550:insensitivity to the type of sampling 1136:As illustrated by this example, in a 852:of getting the disease if exposed is 591:{\displaystyle D_{N}/V_{N}=6/600=.01} 13385: 13085:Accelerated failure time (AFT) model 11039:Correlation does not imply causation 10955:Animal testing on non-human primates 8901:by testing the null hypothesis that 8448:{\displaystyle n_{10}{\hat {\psi }}} 8191:{\displaystyle (n_{10}+n_{01},\pi )} 7318: 6934: 6516: 4445:If we observe data in the form of a 3180:Relation to statistical independence 3176:do not have this symmetry property. 93:that quantifies the strength of the 18: 13397: 12680:Analysis of variance (ANOVA, anova) 11532: 10045: 9290:Phone not used in control interval 9095:{\displaystyle \psi =\pi /(1-\pi )} 7571:The following derivation is due to 5378:{\displaystyle {\hat {\beta }}_{x}} 3922:is greater than the probability of 1560:The odds ratio is the ratio of the 13: 12775:Cochran–Mantel–Haenszel statistics 11401:Pearson product-moment correlation 10423:10.1093/oxfordjournals.aje.a112623 10392:Modern Epidemiology, Third Edition 10352:Gordis Epidemiology, Sixth Edition 9844:Morris JA, Gardner MJ (May 1988). 9814:10.1002/j.1939-4640.2001.tb02212.x 9029:{\displaystyle {\hat {\pi }}_{UB}} 8990:{\displaystyle {\hat {\pi }}_{LB}} 5110: 5107: 5030: 3168:Other measures of effect size for 1217:{\displaystyle V_{N}\approx H_{N}} 1177:{\displaystyle V_{E}\approx H_{E}} 848:The odds ratio is different. The 117:direction is implied (correlation 38:it lacks sufficient corresponding 14: 13485: 10536: 9436:{\displaystyle {\hat {\pi }}=0.5} 9373:Testing the null hypothesis that 6765:) and population log odds ratio ( 6459:assumption is strongly violated. 5349:, then the estimated coefficient 3898:occurring in two groups, denoted 13436: 13424: 13396: 13384: 13372: 13359: 13358: 13149: 10011:European Journal of Epidemiology 9401:{\displaystyle {\hat {\psi }}=1} 9306:Phone not used in crash interval 7072: 5309:and a binary predictor variable 3914:. Thus, when the probability of 2053:= 0 are defined in terms of the 23: 13034:Least-squares spectral analysis 10543:Odds Ratio Calculator – website 10315: 10303: 10254: 10211: 10176: 9646:conditional logistic regression 9472:{\displaystyle \chi ^{2}=13.36} 9319:when not using their phone was 9267:conditional logistic regression 8808:Under the null hypothesis that 6759:joint probability distributions 5281:standard normal random variable 5243: âˆ’ 1.96SE), exp( 1272:{\displaystyle 600\approx 594)} 155:Definition and basic properties 12015:Mean-unbiased minimum-variance 11118: 10922:Pre- and post-test probability 10644:Patient and public involvement 10267:Journal of Clinical Psychology 10002: 9705: 9629: 9617: 9611: 9569: 9421: 9386: 9334: 9287:Phone used in control interval 9249: 9231: 9202: 9172: 9143: 9131: 9089: 9077: 9011: 8972: 8853: 8841: 8797:{\displaystyle {\hat {\psi }}} 8788: 8764:{\displaystyle {\hat {\psi }}} 8755: 8731:{\displaystyle {\hat {\psi }}} 8722: 8693: 8616: 8556: 8528: 8489: 8483: 8439: 8403: 8391: 8382: 8379: 8353: 8331: 8319: 8310: 8299: 8287: 8261: 8237: 8185: 8153: 8100: 8088: 8074: 8028: 8020: 7997: 7943: 7920: 7889: 7861: 7853: 7825: 6424: 6403: 6159: 6147: 6101: 6089: 5809: 5797: 5787: 5761: 5749: 5739: 5704: 5648: 5637: 5581: 5573: 5517: 5506: 5450: 5438: 5425: 5363: 5070: 5053: 5044: 5035: 4900: 4881: 4860: 4841: 4707: 4686: 4652: 4631: 4424: 4411: 4399: 4386: 4357: 4345: 4332: 3794: 3782: 3764: 3760: 3748: 3745: 3713: 3704: 3623: 3611: 3597: 3585: 3582: 3550: 3426: 3407: 3404: 3385: 3370: 3351: 3333: 3314: 3092: 3066: 3046: 3020: 2987: 2961: 2941: 2915: 2537: 2511: 2491: 2465: 2432: 2406: 2386: 2360: 1682: 1663: 1643: 1624: 1266: 1243:{\displaystyle 400\approx 380} 712: 686: 666: 640: 1: 13328:Geographic information system 12544:Simultaneous equations models 10372:Breslow, NE, Day, NE (1980). 10232:10.1016/S0029-7844(01)01488-0 10055:King G, Zeng L (2002-05-30). 9988:10.1016/S1047-2797(01)00278-2 9693: 9295:Phoned used in crash interval 8702:{\displaystyle {\hat {\pi }}} 8625:{\displaystyle {\hat {\pi }}} 7726:{\displaystyle q_{0}=1-p_{0}} 7678:{\displaystyle q_{1}=1-p_{1}} 6588:) and sample log odds ratio ( 6308:Due to the widespread use of 6271:values, such that within the 102: 12511:Coefficient of determination 12122:Uniformly most powerful test 11049:Sex as a biological variable 9907:10.1097/SMJ.0b013e31817a7ee4 9795:Simon S (July–August 2001). 9698: 9272: 7978:is constant across strata. 6512:Estimators of the odds ratio 6495:Invertibility and invariance 6346:"Motivating Example" section 6304:Use in quantitative research 3499: = 1) =  3475: = 1) =  7: 13080:Proportional hazards models 13024:Spectral density estimation 13006:Vector autoregression (VAR) 12440:Maximum posterior estimator 11672:Randomized controlled trial 11013:Intention-to-treat analysis 10985:Analysis of clinical trials 10914:Specificity and sensitivity 10668:Randomized controlled trial 10466:10.1136/bmj.38537.397512.55 10220:Obstetrics & Gynecology 9761:LaMorte WW (May 13, 2013), 9651: 8740:maximum likelihood estimate 8634:maximum likelihood estimate 5298:Role in logistic regression 5275:denotes a probability, and 3848:, we have independence, so 2635: 1827: = 1 âˆ’  10: 13490: 12840:Multivariate distributions 11260:Average absolute deviation 10495: 10261:Taylor HG (January 1975). 9712:Szumilas M (August 2010). 7803:{\displaystyle p_{0}q_{1}} 7766:{\displaystyle p_{1}q_{0}} 7265: 6940:Example of risk reduction 6470:Confusion and exaggeration 3885: 351:developed the disease and 311:{\displaystyle V_{N}=600,} 249:developed the disease and 209:{\displaystyle V_{E}=400,} 13354: 13308: 13245: 13198: 13161: 13157: 13144: 13116: 13098: 13065: 13056: 13014: 12961: 12922: 12871: 12862: 12828:Structural equation model 12783: 12740: 12736: 12711: 12670: 12636: 12590: 12557: 12519: 12486: 12482: 12458: 12398: 12307: 12226: 12190: 12181: 12164:Score/Lagrange multiplier 12149: 12102: 12047: 11973: 11964: 11774: 11770: 11757: 11716: 11690: 11642: 11597: 11579:Sample size determination 11544: 11540: 11527: 11431: 11386: 11360: 11342: 11298: 11250: 11170: 11161: 11157: 11144: 11126: 11057: 11022:Interpretation of results 11021: 10983: 10932: 10882: 10856: 10818: 10788: 10779: 10755:Nested case–control study 10705: 10652: 10599: 10197:10.1001/archderm.141.1.19 9862:10.1136/bmj.296.6632.1313 6806: 6796: 6786: 6776: 6774: 6629: 6619: 6609: 6599: 6597: 6574:Mantel–Haenszel estimator 6332:Relation to relative risk 5913:with a given probability 5237:. This can be mapped to 2055:conditional probabilities 991:is the ratio of the two, 377:{\displaystyle H_{N}=594} 275:{\displaystyle H_{E}=380} 13323:Environmental statistics 12845:Elliptical distributions 12638:Generalized linear model 12567:Simple linear regression 12337:Hodges–Lehmann estimator 11794:Probability distribution 11703:Stochastic approximation 11265:Coefficient of variation 10624:Academic clinical trials 10279:10.1136/bmj.316.7136.989 9945:10.1001/jama.280.19.1690 9895:Southern Medical Journal 9714:"Explaining Odds Ratios" 8920:{\displaystyle \pi =0.5} 7272:There are various other 7099:Absolute risk reduction 6948:Experimental group (E) 6340:Risk ratio vs odds ratio 6267:of units with different 1873:probability distribution 242:{\displaystyle D_{E}=20} 119:does not imply causation 12983:Cross-correlation (XCF) 12591:Non-standard predictors 12025:Lehmann–ScheffĂŠ theorem 11698:Adaptive clinical trial 10842:Relative risk reduction 10690:Adaptive clinical trial 10634:Evidence-based medicine 10617:Adaptive clinical trial 10185:Archives of Dermatology 9502:{\displaystyle \psi =1} 8894:{\displaystyle \psi =1} 7168:Relative risk reduction 6354:rare disease assumption 5263: < âˆ’| 2322:Thus the odds ratio is 1403: Not exposed  440: Not exposed  344:{\displaystyle D_{N}=6} 175:rare disease assumption 145:plays an important role 138:rare disease assumption 130:absolute risk reduction 53:more precise citations. 13379:Mathematics portal 13200:Engineering statistics 13108:Nelson–Aalen estimator 12685:Analysis of covariance 12572:Ordinary least squares 12496:Pearson product-moment 11900:Statistical functional 11811:Empirical distribution 11644:Controlled experiments 11373:Frequency distribution 11151:Descriptive statistics 10830:Number needed to treat 10064:Statistics in Medicine 9976:Annals of Epidemiology 9636: 9554: 9534: 9503: 9473: 9437: 9402: 9364: 9256: 9116: 9096: 9056:, respectively. Since 9050: 9030: 8991: 8952: 8921: 8895: 8866: 8798: 8765: 8732: 8703: 8670: 8650: 8626: 8594: 8535: 8449: 8410: 8338: 8216: 8192: 8136: 8135:{\displaystyle n_{10}} 8107: 7972: 7950: 7804: 7767: 7727: 7679: 7631: 7602: 7562: 7561:{\displaystyle n_{00}} 7535: 7534:{\displaystyle n_{01}} 7508: 7507:{\displaystyle n_{10}} 7481: 7480:{\displaystyle n_{11}} 7449: 7448:{\displaystyle n_{00}} 7421: 7420:{\displaystyle n_{01}} 7388: 7387:{\displaystyle n_{10}} 7360: 7359:{\displaystyle n_{11}} 7121:Number needed to treat 6563:Alternative estimators 6434: 6341: 6208: 5888: 5816: 5768: 5717: 5379: 5212: 5081: 4992: 4727: 4565: 4436: 4240: 4200: 4094: 4024: 3931: 3832: 3633: 3437: 3159: 2877: 2599: 2313: 2004: 1849:equals zero, i.e., if 1811: 1534: 1507: 1480: 1424: 1341: 1314: 1273: 1244: 1218: 1178: 1127: 981: 911: 839: 592: 530: 461: 378: 345: 312: 276: 243: 210: 13295:Population statistics 13237:System identification 12971:Autocorrelation (ACF) 12899:Exponential smoothing 12813:Discriminant analysis 12808:Canonical correlation 12672:Partition of variance 12534:Regression validation 12378:(Jonckheere–Terpstra) 12277:Likelihood-ratio test 11966:Frequentist inference 11878:Location–scale family 11799:Sampling distribution 11764:Statistical inference 11731:Cross-sectional study 11718:Observational studies 11677:Randomized experiment 11506:Stem-and-leaf display 11308:Central limit theorem 10834:Number needed to harm 10721:Cross-sectional study 10673:Scientific experiment 10629:Clinical study design 10152:10.3399/bjgp12X630223 9668:Diagnostic odds ratio 9637: 9555: 9553:{\displaystyle \psi } 9535: 9504: 9474: 9438: 9403: 9365: 9257: 9117: 9115:{\displaystyle \psi } 9097: 9051: 9031: 8992: 8953: 8927:. This is done using 8922: 8896: 8867: 8799: 8766: 8733: 8704: 8671: 8669:{\displaystyle \psi } 8651: 8627: 8595: 8536: 8450: 8411: 8339: 8217: 8193: 8137: 8108: 7973: 7971:{\displaystyle \psi } 7951: 7805: 7768: 7728: 7680: 7632: 7630:{\displaystyle p_{0}} 7603: 7601:{\displaystyle p_{1}} 7563: 7536: 7509: 7482: 7450: 7422: 7389: 7361: 6435: 6339: 6209: 5889: 5817: 5769: 5718: 5380: 5213: 5082: 4993: 4728: 4566: 4437: 4237: 4230:Statistical inference 4201: 4095: 4025: 3893: 3833: 3634: 3518:differs from 1, then 3514:. If the odds ratio 3438: 3160: 2878: 2600: 2314: 2005: 1812: 1535: 1533:{\displaystyle V_{N}} 1508: 1506:{\displaystyle V_{E}} 1481: 1425: 1342: 1340:{\displaystyle V_{N}} 1315: 1313:{\displaystyle V_{E}} 1274: 1245: 1219: 1179: 1128: 982: 912: 840: 593: 531: 462: 379: 346: 313: 277: 244: 211: 13218:Probabilistic design 12803:Principal components 12646:Exponential families 12598:Nonlinear regression 12577:General linear model 12539:Mixed effects models 12529:Errors and residuals 12506:Confounding variable 12408:Bayesian probability 12386:Van der Waerden test 12376:Ordered alternative 12141:Multiple comparisons 12020:Rao–Blackwellization 11983:Estimating equations 11939:Statistical distance 11657:Factorial experiment 11190:Arithmetic-Geometric 10800:Cumulative incidence 9801:Journal of Andrology 9764:Case-Control Studies 9566: 9544: 9533:{\displaystyle \pi } 9524: 9487: 9450: 9412: 9377: 9325: 9128: 9106: 9060: 9049:{\displaystyle \pi } 9040: 9001: 8962: 8951:{\displaystyle \pi } 8942: 8905: 8879: 8812: 8779: 8746: 8713: 8684: 8660: 8649:{\displaystyle \pi } 8640: 8607: 8547: 8461: 8420: 8350: 8228: 8215:{\displaystyle \pi } 8206: 8150: 8119: 8115:The distribution of 7988: 7962: 7816: 7777: 7740: 7691: 7643: 7614: 7585: 7545: 7518: 7491: 7464: 7432: 7404: 7371: 7343: 6367: 6344:As explained in the 6326:case-control studies 5938: 5856: 5778: 5730: 5396: 5353: 5247: + 1.96SE) 5101: 5013: 4810: 4581: 4455: 4257: 4111: 4040: 3942: 3693: 3525: 3239: 2893: 2651: 2329: 2087: 1894: 1594: 1517: 1490: 1437: 1368: Diseased  1358: 1324: 1297: 1254: 1228: 1188: 1148: 998: 925: 856: 611: 540: 478: 405: Diseased  395: 355: 322: 286: 253: 220: 184: 134:case-control studies 13469:Bayesian statistics 13290:Official statistics 13213:Methods engineering 12894:Seasonal adjustment 12662:Poisson regressions 12582:Bayesian regression 12521:Regression analysis 12501:Partial correlation 12473:Regression analysis 12072:Prediction interval 12067:Likelihood interval 12057:Confidence interval 12049:Interval estimation 12010:Unbiased estimators 11828:Model specification 11708:Up-and-down designs 11396:Partial correlation 11352:Index of dispersion 11270:Interquartile range 10707:Observational study 10639:Real world evidence 10593:experimental design 10324:Modern Epidemiology 9518:confidence interval 8936:confidence interval 8738:is the conditional 7002:Total subjects (S) 6941: 6814: = âˆ’0.41 6810: = 0.67, 6637: = âˆ’1.39 6633: = 0.25, 6570:Fisher's exact test 6310:logistic regression 5830:when the values of 5303:Logistic regression 5235: Âą 1.96SE 5228:confidence interval 3926:occurring in group 3918:occurring in group 1384: Exposed  1375: Healthy  421: Exposed  412: Healthy  13464:Medical statistics 13310:Spatial statistics 13190:Medical statistics 13090:First hitting time 13044:Whittle likelihood 12695:Degrees of freedom 12690:Multivariate ANOVA 12623:Heteroscedasticity 12435:Bayesian estimator 12400:Bayesian inference 12249:Kolmogorov–Smirnov 12134:Randomization test 12104:Testing hypotheses 12077:Tolerance interval 11988:Maximum likelihood 11883:Exponential family 11816:Density estimation 11776:Statistical theory 11736:Natural experiment 11682:Scientific control 11599:Survey methodology 11285:Standard deviation 10993:Risk–benefit ratio 10960:First-in-man study 10910:Case fatality rate 10751:Case–control study 10725:Longitudinal study 10023:10.1007/BF01721219 9632: 9550: 9530: 9499: 9469: 9433: 9398: 9360: 9284:Case-control pairs 9252: 9112: 9092: 9046: 9026: 8987: 8948: 8917: 8891: 8862: 8794: 8761: 8728: 8709:. It follows that 8699: 8678:monotonic function 8666: 8646: 8622: 8590: 8531: 8445: 8406: 8334: 8212: 8200:maximum likelihood 8188: 8132: 8103: 7968: 7946: 7800: 7763: 7723: 7675: 7627: 7598: 7558: 7531: 7504: 7477: 7445: 7417: 7384: 7356: 7332:Control unexposed 7326:Case-control pairs 7308:case-control study 7262:Related statistics 6939: 6804: = 2.77 6627: = 1.39 6580:Numerical examples 6430: 6342: 6265:convenience sample 6204: 6202: 5884: 5812: 5764: 5713: 5375: 5208: 5203: 5181: 5159: 5137: 5077: 4988: 4981: 4914: 4723: 4721: 4561: 4559: 4432: 4241: 4224:natural logarithms 4196: 4090: 4020: 4018: 3932: 3841:In the case where 3828: 3629: 3433: 3431: 3155: 3150: 3097: 2992: 2873: 2871: 2595: 2542: 2437: 2309: 2307: 2000: 1998: 1807: 1580:(first group) and 1530: 1503: 1476: 1420: 1418: 1349:case-control study 1337: 1310: 1269: 1240: 1214: 1174: 1123: 977: 907: 835: 588: 526: 457: 455: 374: 341: 308: 272: 239: 206: 13412: 13411: 13350: 13349: 13346: 13345: 13285:National accounts 13255:Actuarial science 13247:Social statistics 13140: 13139: 13136: 13135: 13132: 13131: 13067:Survival function 13052: 13051: 12914:Granger causality 12755:Contingency table 12730:Survival analysis 12707: 12706: 12703: 12702: 12559:Linear regression 12454: 12453: 12450: 12449: 12425:Credible interval 12394: 12393: 12177: 12176: 11993:Method of moments 11862:Parametric family 11823:Statistical model 11753: 11752: 11749: 11748: 11667:Random assignment 11589:Statistical power 11523: 11522: 11519: 11518: 11368:Contingency table 11338: 11337: 11205:Generalized/power 11086: 11085: 11034:Survivorship bias 10998:Systematic review 10965:Multicenter trial 10928: 10927: 10918:Likelihood-ratios 10890:Clinical endpoint 10858:Population impact 10812:Period prevalence 10589:Clinical research 10333:978-0-7817-5564-1 10070:(10): 1409–1427. 9609: 9588: 9424: 9389: 9337: 9316: 9315: 9247: 9234: 9205: 9188: 9175: 9146: 9014: 8975: 8791: 8758: 8725: 8696: 8619: 8559: 8486: 8442: 8394: 8322: 8302: 8240: 7458: 7457: 7319:Matched 2x2 Table 7259: 7258: 7206: 7077: 7076: 6935:Numerical example 6932: 6931: 6800: = 16, 6755: 6754: 6555:and exhibit high 6523:sample odds ratio 6517:Sample odds ratio 6428: 6422: 6382: 6373: 6198: 6140: 6069: 6023: 5924:with probability 5872: 5800: 5752: 5708: 5366: 5205: 5202: 5180: 5158: 5136: 5027: 5021: 4980: 4913: 4903: 4884: 4863: 4844: 4710: 4689: 4655: 4634: 4447:contingency table 4317: 4248:natural logarithm 4188: 4175: 4142: 4082: 3823: 3627: 3149: 3096: 2991: 2867: 2826: 2772: 2731: 2593: 2541: 2436: 2303: 2262: 2208: 2167: 1802: 1747: 1686: 1468: 1404: 1385: 1376: 1369: 1138:rare-disease case 1111: 1098: 1065: 1004: 823: 810: 777: 716: 617: 441: 422: 413: 406: 386:contingency table 79: 78: 71: 13481: 13441: 13440: 13429: 13428: 13427: 13420: 13400: 13399: 13388: 13387: 13377: 13376: 13362: 13361: 13265:Crime statistics 13159: 13158: 13146: 13145: 13063: 13062: 13029:Fourier analysis 13016:Frequency domain 12996: 12943: 12909:Structural break 12869: 12868: 12818:Cluster analysis 12765:Log-linear model 12738: 12737: 12713: 12712: 12654: 12628:Homoscedasticity 12484: 12483: 12460: 12459: 12379: 12371: 12363: 12362:(Kruskal–Wallis) 12347: 12332: 12287:Cross validation 12272: 12254:Anderson–Darling 12201: 12188: 12187: 12159:Likelihood-ratio 12151:Parametric tests 12129:Permutation test 12112:1- & 2-tails 12003:Minimum distance 11975:Point estimation 11971: 11970: 11922:Optimal decision 11873: 11772: 11771: 11759: 11758: 11741:Quasi-experiment 11691:Adaptive designs 11542: 11541: 11529: 11528: 11406:Rank correlation 11168: 11167: 11159: 11158: 11146: 11145: 11113: 11106: 11099: 11090: 11089: 10933:Trial/test types 10808:Point prevalence 10786: 10785: 10729:Ecological study 10712:EBM II-2 to II-3 10683:Open-label trial 10678:Blind experiment 10654:Controlled study 10582: 10575: 10568: 10559: 10558: 10531: 10489: 10488: 10478: 10468: 10444: 10435: 10434: 10402: 10396: 10395: 10387: 10378: 10377: 10369: 10356: 10355: 10347: 10338: 10337: 10319: 10313: 10307: 10301: 10300: 10290: 10258: 10252: 10251: 10215: 10209: 10208: 10180: 10174: 10173: 10163: 10131: 10122: 10121: 10113: 10104: 10103: 10076:10.1002/sim.1032 10061: 10052: 10043: 10042: 10006: 10000: 9999: 9971: 9965: 9964: 9928: 9919: 9918: 9890: 9884: 9883: 9873: 9856:(6632): 1313–6. 9841: 9835: 9834: 9816: 9792: 9783: 9782: 9781: 9780: 9771:, archived from 9758: 9752: 9751: 9741: 9709: 9683:Likelihood ratio 9641: 9639: 9638: 9633: 9610: 9608: 9594: 9589: 9587: 9573: 9559: 9557: 9556: 9551: 9539: 9537: 9536: 9531: 9508: 9506: 9505: 9500: 9478: 9476: 9475: 9470: 9462: 9461: 9442: 9440: 9439: 9434: 9426: 9425: 9417: 9407: 9405: 9404: 9399: 9391: 9390: 9382: 9369: 9367: 9366: 9361: 9350: 9339: 9338: 9330: 9281: 9280: 9261: 9259: 9258: 9253: 9248: 9246: 9245: 9244: 9236: 9235: 9227: 9216: 9215: 9207: 9206: 9198: 9194: 9189: 9187: 9186: 9185: 9177: 9176: 9168: 9157: 9156: 9148: 9147: 9139: 9135: 9121: 9119: 9118: 9113: 9101: 9099: 9098: 9093: 9076: 9055: 9053: 9052: 9047: 9035: 9033: 9032: 9027: 9025: 9024: 9016: 9015: 9007: 8996: 8994: 8993: 8988: 8986: 8985: 8977: 8976: 8968: 8957: 8955: 8954: 8949: 8926: 8924: 8923: 8918: 8900: 8898: 8897: 8892: 8871: 8869: 8868: 8863: 8840: 8803: 8801: 8800: 8795: 8793: 8792: 8784: 8770: 8768: 8767: 8762: 8760: 8759: 8751: 8737: 8735: 8734: 8729: 8727: 8726: 8718: 8708: 8706: 8705: 8700: 8698: 8697: 8689: 8675: 8673: 8672: 8667: 8655: 8653: 8652: 8647: 8631: 8629: 8628: 8623: 8621: 8620: 8612: 8599: 8597: 8596: 8591: 8589: 8588: 8579: 8574: 8573: 8561: 8560: 8552: 8540: 8538: 8537: 8532: 8527: 8526: 8514: 8513: 8501: 8500: 8488: 8487: 8479: 8473: 8472: 8454: 8452: 8451: 8446: 8444: 8443: 8435: 8432: 8431: 8416:and subtracting 8415: 8413: 8412: 8407: 8396: 8395: 8387: 8378: 8377: 8365: 8364: 8343: 8341: 8340: 8335: 8324: 8323: 8315: 8309: 8304: 8303: 8295: 8286: 8285: 8273: 8272: 8260: 8255: 8254: 8242: 8241: 8233: 8221: 8219: 8218: 8213: 8197: 8195: 8194: 8189: 8178: 8177: 8165: 8164: 8141: 8139: 8138: 8133: 8131: 8130: 8112: 8110: 8109: 8104: 8087: 8073: 8072: 8063: 8062: 8050: 8049: 8040: 8039: 8027: 8019: 8018: 8009: 8008: 7977: 7975: 7974: 7969: 7955: 7953: 7952: 7947: 7942: 7941: 7932: 7931: 7919: 7914: 7913: 7904: 7903: 7888: 7887: 7878: 7873: 7872: 7860: 7852: 7851: 7842: 7837: 7836: 7809: 7807: 7806: 7801: 7799: 7798: 7789: 7788: 7772: 7770: 7769: 7764: 7762: 7761: 7752: 7751: 7732: 7730: 7729: 7724: 7722: 7721: 7703: 7702: 7684: 7682: 7681: 7676: 7674: 7673: 7655: 7654: 7636: 7634: 7633: 7628: 7626: 7625: 7607: 7605: 7604: 7599: 7597: 7596: 7567: 7565: 7564: 7559: 7557: 7556: 7540: 7538: 7537: 7532: 7530: 7529: 7513: 7511: 7510: 7505: 7503: 7502: 7486: 7484: 7483: 7478: 7476: 7475: 7454: 7452: 7451: 7446: 7444: 7443: 7426: 7424: 7423: 7418: 7416: 7415: 7393: 7391: 7390: 7385: 7383: 7382: 7365: 7363: 7362: 7357: 7355: 7354: 7323: 7322: 7204: 7079: 7078: 7038:Event rate (ER) 6942: 6938: 6790: = 1, 6780: = 1, 6772: 6623: = 4, 6613: = 1, 6603: = 1, 6595: 6439: 6437: 6436: 6431: 6429: 6427: 6423: 6420: 6415: 6414: 6399: 6398: 6380: 6379: 6374: 6371: 6284: 6277: 6247: 6213: 6211: 6210: 6205: 6203: 6199: 6197: 6196: 6195: 6183: 6182: 6172: 6171: 6170: 6145: 6141: 6139: 6138: 6137: 6125: 6124: 6114: 6113: 6112: 6087: 6070: 6068: 6067: 6066: 6054: 6053: 6043: 6042: 6041: 6028: 6024: 6022: 6021: 6020: 6008: 6007: 5997: 5996: 5995: 5982: 5944: 5930: 5923: 5912: 5893: 5891: 5890: 5885: 5883: 5882: 5874: 5873: 5868: 5862: 5844:are held fixed. 5821: 5819: 5818: 5813: 5808: 5807: 5802: 5801: 5793: 5773: 5771: 5770: 5765: 5760: 5759: 5754: 5753: 5745: 5722: 5720: 5719: 5714: 5709: 5707: 5703: 5702: 5684: 5683: 5644: 5636: 5635: 5617: 5616: 5576: 5572: 5571: 5553: 5552: 5513: 5505: 5504: 5486: 5485: 5445: 5437: 5436: 5415: 5414: 5413: 5412: 5384: 5382: 5381: 5376: 5374: 5373: 5368: 5367: 5359: 5270: 5268: 5248: 5236: 5217: 5215: 5214: 5209: 5207: 5206: 5204: 5201: 5200: 5188: 5182: 5179: 5178: 5166: 5160: 5157: 5156: 5144: 5138: 5135: 5134: 5122: 5119: 5114: 5113: 5086: 5084: 5083: 5078: 5069: 5068: 5034: 5033: 5025: 5019: 4997: 4995: 4994: 4989: 4987: 4986: 4982: 4979: 4978: 4977: 4968: 4967: 4957: 4956: 4955: 4946: 4945: 4935: 4919: 4915: 4912: 4911: 4910: 4905: 4904: 4896: 4892: 4891: 4886: 4885: 4877: 4872: 4871: 4870: 4865: 4864: 4856: 4852: 4851: 4846: 4845: 4837: 4832: 4802: 4768: 4749: 4748: 4747: 4742: 4732: 4730: 4729: 4724: 4722: 4718: 4717: 4712: 4711: 4703: 4697: 4696: 4691: 4690: 4682: 4663: 4662: 4657: 4656: 4648: 4642: 4641: 4636: 4635: 4627: 4587: 4570: 4568: 4567: 4562: 4560: 4556: 4555: 4544: 4543: 4519: 4518: 4507: 4506: 4461: 4441: 4439: 4438: 4433: 4427: 4423: 4422: 4398: 4397: 4376: 4375: 4369: 4368: 4344: 4343: 4322: 4318: 4316: 4315: 4314: 4305: 4304: 4294: 4293: 4292: 4283: 4282: 4272: 4205: 4203: 4202: 4197: 4189: 4181: 4176: 4174: 4161: 4148: 4143: 4141: 4137: 4128: 4124: 4115: 4099: 4097: 4096: 4091: 4083: 4081: 4068: 4055: 4050: 4029: 4027: 4026: 4021: 4019: 3948: 3881: 3869: 3847: 3837: 3835: 3834: 3829: 3824: 3822: 3821: 3809: 3808: 3772: 3771: 3744: 3743: 3728: 3727: 3703: 3685: 3638: 3636: 3635: 3630: 3628: 3626: 3606: 3581: 3580: 3565: 3564: 3542: 3537: 3536: 3513: 3489: 3442: 3440: 3439: 3434: 3432: 3425: 3424: 3403: 3402: 3382: 3381: 3369: 3368: 3332: 3331: 3313: 3312: 3301: 3300: 3291: 3290: 3245: 3231: 3211: 3164: 3162: 3161: 3156: 3151: 3148: 3147: 3146: 3137: 3136: 3126: 3125: 3124: 3115: 3114: 3104: 3098: 3095: 3091: 3090: 3078: 3077: 3065: 3060: 3059: 3049: 3045: 3044: 3032: 3031: 3019: 3014: 3013: 3003: 3000: 2999: 2993: 2990: 2986: 2985: 2973: 2972: 2960: 2955: 2954: 2944: 2940: 2939: 2927: 2926: 2914: 2909: 2908: 2898: 2882: 2880: 2879: 2874: 2872: 2868: 2866: 2865: 2864: 2852: 2851: 2841: 2840: 2831: 2827: 2825: 2824: 2823: 2811: 2810: 2800: 2799: 2790: 2773: 2771: 2770: 2769: 2757: 2756: 2746: 2745: 2736: 2732: 2730: 2729: 2728: 2716: 2715: 2705: 2704: 2695: 2657: 2631: 2629: 2625: 2619: 2617: 2613: 2604: 2602: 2601: 2596: 2594: 2592: 2591: 2590: 2581: 2580: 2570: 2569: 2568: 2559: 2558: 2548: 2543: 2540: 2536: 2535: 2523: 2522: 2510: 2505: 2504: 2494: 2490: 2489: 2477: 2476: 2464: 2459: 2458: 2448: 2445: 2444: 2438: 2435: 2431: 2430: 2418: 2417: 2405: 2400: 2399: 2389: 2385: 2384: 2372: 2371: 2359: 2354: 2353: 2343: 2318: 2316: 2315: 2310: 2308: 2304: 2302: 2301: 2300: 2288: 2287: 2277: 2276: 2267: 2263: 2261: 2260: 2259: 2247: 2246: 2236: 2235: 2226: 2209: 2207: 2206: 2205: 2193: 2192: 2182: 2181: 2172: 2168: 2166: 2165: 2164: 2152: 2151: 2141: 2140: 2131: 2093: 2079: 2060: 2052: 2048: 2044: 2037: 2030: 2023: 2016: 2009: 2007: 2006: 2001: 1999: 1995: 1994: 1983: 1982: 1958: 1957: 1946: 1945: 1900: 1886: 1882: 1877:random variables 1816: 1814: 1813: 1808: 1803: 1801: 1799: 1798: 1789: 1788: 1777: 1775: 1774: 1765: 1764: 1753: 1748: 1746: 1745: 1744: 1735: 1730: 1729: 1719: 1718: 1717: 1708: 1703: 1702: 1692: 1687: 1685: 1681: 1680: 1662: 1657: 1656: 1646: 1642: 1641: 1623: 1618: 1617: 1607: 1539: 1537: 1536: 1531: 1529: 1528: 1512: 1510: 1509: 1504: 1502: 1501: 1485: 1483: 1482: 1477: 1469: 1467: 1463: 1454: 1450: 1441: 1429: 1427: 1426: 1421: 1419: 1405: 1402: 1386: 1383: 1377: 1374: 1370: 1367: 1364: 1346: 1344: 1343: 1338: 1336: 1335: 1319: 1317: 1316: 1311: 1309: 1308: 1278: 1276: 1275: 1270: 1249: 1247: 1246: 1241: 1223: 1221: 1220: 1215: 1213: 1212: 1200: 1199: 1183: 1181: 1180: 1175: 1173: 1172: 1160: 1159: 1132: 1130: 1129: 1124: 1112: 1104: 1099: 1097: 1093: 1084: 1080: 1071: 1066: 1064: 1063: 1062: 1053: 1048: 1047: 1037: 1036: 1035: 1026: 1021: 1020: 1010: 1005: 1002: 986: 984: 983: 978: 963: 952: 951: 942: 937: 936: 917:and the odds if 916: 914: 913: 908: 894: 883: 882: 873: 868: 867: 844: 842: 841: 836: 824: 816: 811: 809: 805: 796: 792: 783: 778: 776: 775: 774: 765: 760: 759: 749: 748: 747: 738: 733: 732: 722: 717: 715: 711: 710: 698: 697: 685: 680: 679: 669: 665: 664: 652: 651: 639: 634: 633: 623: 618: 615: 597: 595: 594: 589: 578: 567: 566: 557: 552: 551: 535: 533: 532: 527: 516: 505: 504: 495: 490: 489: 466: 464: 463: 458: 456: 442: 439: 423: 420: 414: 411: 407: 404: 401: 383: 381: 380: 375: 367: 366: 350: 348: 347: 342: 334: 333: 317: 315: 314: 309: 298: 297: 281: 279: 278: 273: 265: 264: 248: 246: 245: 240: 232: 231: 215: 213: 212: 207: 196: 195: 74: 67: 63: 60: 54: 49:this article by 40:inline citations 27: 26: 19: 13489: 13488: 13484: 13483: 13482: 13480: 13479: 13478: 13449: 13448: 13447: 13435: 13425: 13423: 13415: 13413: 13408: 13371: 13342: 13304: 13241: 13227:quality control 13194: 13176:Clinical trials 13153: 13128: 13112: 13100:Hazard function 13094: 13048: 13010: 12994: 12957: 12953:Breusch–Godfrey 12941: 12918: 12858: 12833:Factor analysis 12779: 12760:Graphical model 12732: 12699: 12666: 12652: 12632: 12586: 12553: 12515: 12478: 12477: 12446: 12390: 12377: 12369: 12361: 12345: 12330: 12309:Rank statistics 12303: 12282:Model selection 12270: 12228:Goodness of fit 12222: 12199: 12173: 12145: 12098: 12043: 12032:Median unbiased 11960: 11871: 11804:Order statistic 11766: 11745: 11712: 11686: 11638: 11593: 11536: 11534:Data collection 11515: 11427: 11382: 11356: 11334: 11294: 11246: 11163:Continuous data 11153: 11140: 11122: 11117: 11087: 11082: 11053: 11017: 10979: 10924: 10878: 10852: 10826:Risk difference 10814: 10775: 10709: 10701: 10656: 10648: 10612:Trial protocols 10595: 10586: 10539: 10534: 10520:10.2307/2982448 10510:. A (General). 10498: 10493: 10492: 10445: 10438: 10403: 10399: 10388: 10381: 10370: 10359: 10348: 10341: 10334: 10320: 10316: 10308: 10304: 10259: 10255: 10216: 10212: 10181: 10177: 10146:(596): e220-3. 10132: 10125: 10114: 10107: 10059: 10053: 10046: 10007: 10003: 9972: 9968: 9929: 9922: 9891: 9887: 9842: 9838: 9793: 9786: 9778: 9776: 9759: 9755: 9710: 9706: 9701: 9696: 9654: 9598: 9593: 9577: 9572: 9567: 9564: 9563: 9545: 9542: 9541: 9525: 9522: 9521: 9488: 9485: 9484: 9457: 9453: 9451: 9448: 9447: 9416: 9415: 9413: 9410: 9409: 9381: 9380: 9378: 9375: 9374: 9346: 9329: 9328: 9326: 9323: 9322: 9275: 9237: 9226: 9225: 9224: 9217: 9208: 9197: 9196: 9195: 9193: 9178: 9167: 9166: 9165: 9158: 9149: 9138: 9137: 9136: 9134: 9129: 9126: 9125: 9107: 9104: 9103: 9072: 9061: 9058: 9057: 9041: 9038: 9037: 9017: 9006: 9005: 9004: 9002: 8999: 8998: 8978: 8967: 8966: 8965: 8963: 8960: 8959: 8943: 8940: 8939: 8906: 8903: 8902: 8880: 8877: 8876: 8836: 8813: 8810: 8809: 8783: 8782: 8780: 8777: 8776: 8750: 8749: 8747: 8744: 8743: 8717: 8716: 8714: 8711: 8710: 8688: 8687: 8685: 8682: 8681: 8661: 8658: 8657: 8641: 8638: 8637: 8611: 8610: 8608: 8605: 8604: 8584: 8580: 8575: 8569: 8565: 8551: 8550: 8548: 8545: 8544: 8522: 8518: 8509: 8505: 8496: 8492: 8478: 8477: 8468: 8464: 8462: 8459: 8458: 8434: 8433: 8427: 8423: 8421: 8418: 8417: 8386: 8385: 8373: 8369: 8360: 8356: 8351: 8348: 8347: 8314: 8313: 8305: 8294: 8293: 8281: 8277: 8268: 8264: 8256: 8250: 8246: 8232: 8231: 8229: 8226: 8225: 8207: 8204: 8203: 8173: 8169: 8160: 8156: 8151: 8148: 8147: 8146: ~  B 8126: 8122: 8120: 8117: 8116: 8083: 8068: 8064: 8058: 8054: 8045: 8041: 8035: 8031: 8023: 8014: 8010: 8004: 8000: 7989: 7986: 7985: 7963: 7960: 7959: 7958:We assume that 7937: 7933: 7927: 7923: 7915: 7909: 7905: 7899: 7895: 7883: 7879: 7874: 7868: 7864: 7856: 7847: 7843: 7838: 7832: 7828: 7817: 7814: 7813: 7794: 7790: 7784: 7780: 7778: 7775: 7774: 7757: 7753: 7747: 7743: 7741: 7738: 7737: 7717: 7713: 7698: 7694: 7692: 7689: 7688: 7669: 7665: 7650: 7646: 7644: 7641: 7640: 7621: 7617: 7615: 7612: 7611: 7592: 7588: 7586: 7583: 7582: 7552: 7548: 7546: 7543: 7542: 7525: 7521: 7519: 7516: 7515: 7498: 7494: 7492: 7489: 7488: 7471: 7467: 7465: 7462: 7461: 7439: 7435: 7433: 7430: 7429: 7411: 7407: 7405: 7402: 7401: 7378: 7374: 7372: 7369: 7368: 7350: 7346: 7344: 7341: 7340: 7329:Control exposed 7321: 7304: 7270: 7264: 7187:, or 1 − 6982:Non-events (N) 6937: 6904: = 0 6872: = 1 6864: = 0 6858: = 1 6852: = 0 6846: = 1 6840: = 0 6834: = 1 6828: = 0 6822: = 1 6794: = 0 6784: = 0 6727: = 0 6695: = 1 6687: = 0 6681: = 1 6675: = 0 6669: = 1 6663: = 0 6657: = 1 6651: = 0 6645: = 1 6617: = 0 6607: = 0 6582: 6565: 6549: 6543: 6536: 6530: 6519: 6514: 6497: 6472: 6451: 6419: 6410: 6406: 6394: 6390: 6383: 6378: 6370: 6368: 6365: 6364: 6334: 6322:clinical trials 6314:survey research 6306: 6285:subsamples the 6279: 6272: 6246: 6240: 6233: 6227: 6221: 6201: 6200: 6191: 6187: 6178: 6174: 6173: 6166: 6162: 6146: 6144: 6142: 6133: 6129: 6120: 6116: 6115: 6108: 6104: 6088: 6086: 6084: 6072: 6071: 6062: 6058: 6049: 6045: 6044: 6037: 6033: 6029: 6027: 6025: 6016: 6012: 6003: 5999: 5998: 5991: 5987: 5983: 5981: 5979: 5967: 5966: 5955: 5941: 5939: 5936: 5935: 5925: 5918: 5907: 5875: 5863: 5861: 5860: 5859: 5857: 5854: 5853: 5850: 5842: 5836: 5803: 5792: 5791: 5790: 5779: 5776: 5775: 5755: 5744: 5743: 5742: 5731: 5728: 5727: 5698: 5694: 5679: 5675: 5640: 5631: 5627: 5612: 5608: 5577: 5567: 5563: 5548: 5544: 5509: 5500: 5496: 5481: 5477: 5446: 5444: 5432: 5428: 5408: 5404: 5403: 5399: 5397: 5394: 5393: 5369: 5358: 5357: 5356: 5354: 5351: 5350: 5347: 5340: 5325: 5319: 5300: 5264: 5254: 5238: 5231: 5196: 5192: 5186: 5174: 5170: 5164: 5152: 5148: 5142: 5130: 5126: 5120: 5118: 5106: 5105: 5104: 5102: 5099: 5098: 5064: 5060: 5029: 5028: 5014: 5011: 5010: 4973: 4969: 4963: 4959: 4958: 4951: 4947: 4941: 4937: 4936: 4933: 4929: 4906: 4895: 4894: 4893: 4887: 4876: 4875: 4874: 4873: 4866: 4855: 4854: 4853: 4847: 4836: 4835: 4834: 4833: 4830: 4826: 4813: 4811: 4808: 4807: 4801: 4794: 4787: 4780: 4770: 4763: 4754: 4743: 4740: 4739: 4738: 4737: 4720: 4719: 4713: 4702: 4701: 4700: 4698: 4692: 4681: 4680: 4679: 4677: 4665: 4664: 4658: 4647: 4646: 4645: 4643: 4637: 4626: 4625: 4624: 4622: 4610: 4609: 4598: 4584: 4582: 4579: 4578: 4558: 4557: 4551: 4547: 4545: 4539: 4535: 4533: 4521: 4520: 4514: 4510: 4508: 4502: 4498: 4496: 4484: 4483: 4472: 4458: 4456: 4453: 4452: 4418: 4414: 4393: 4389: 4371: 4370: 4364: 4360: 4339: 4335: 4310: 4306: 4300: 4296: 4295: 4288: 4284: 4278: 4274: 4273: 4271: 4267: 4260: 4258: 4255: 4254: 4232: 4180: 4162: 4149: 4147: 4133: 4129: 4120: 4116: 4114: 4112: 4109: 4108: 4069: 4056: 4054: 4043: 4041: 4038: 4037: 4017: 4016: 4011: 4006: 3994: 3993: 3988: 3983: 3971: 3970: 3959: 3945: 3943: 3940: 3939: 3888: 3880: 3874: 3868: 3862: 3855: 3849: 3842: 3814: 3810: 3801: 3797: 3767: 3763: 3736: 3732: 3720: 3716: 3702: 3694: 3691: 3690: 3684: 3677: 3670: 3663: 3656: 3649: 3643: 3607: 3573: 3569: 3557: 3553: 3543: 3541: 3532: 3528: 3526: 3523: 3522: 3512: 3505: 3491: 3488: 3481: 3467: 3464: 3430: 3429: 3420: 3416: 3398: 3394: 3383: 3377: 3373: 3364: 3360: 3349: 3337: 3336: 3327: 3323: 3308: 3304: 3302: 3296: 3292: 3286: 3282: 3280: 3268: 3267: 3256: 3242: 3240: 3237: 3236: 3230: = 1) 3221: 3213: 3210: = 1) 3201: 3193: 3182: 3142: 3138: 3132: 3128: 3127: 3120: 3116: 3110: 3106: 3105: 3102: 3086: 3082: 3073: 3069: 3061: 3055: 3051: 3050: 3040: 3036: 3027: 3023: 3015: 3009: 3005: 3004: 3001: 2995: 2994: 2981: 2977: 2968: 2964: 2956: 2950: 2946: 2945: 2935: 2931: 2922: 2918: 2910: 2904: 2900: 2899: 2896: 2894: 2891: 2890: 2870: 2869: 2860: 2856: 2847: 2843: 2842: 2836: 2832: 2830: 2828: 2819: 2815: 2806: 2802: 2801: 2795: 2791: 2789: 2787: 2775: 2774: 2765: 2761: 2752: 2748: 2747: 2741: 2737: 2735: 2733: 2724: 2720: 2711: 2707: 2706: 2700: 2696: 2694: 2692: 2680: 2679: 2668: 2654: 2652: 2649: 2648: 2638: 2627: 2623: 2621: 2615: 2611: 2609: 2586: 2582: 2576: 2572: 2571: 2564: 2560: 2554: 2550: 2549: 2547: 2531: 2527: 2518: 2514: 2506: 2500: 2496: 2495: 2485: 2481: 2472: 2468: 2460: 2454: 2450: 2449: 2446: 2440: 2439: 2426: 2422: 2413: 2409: 2401: 2395: 2391: 2390: 2380: 2376: 2367: 2363: 2355: 2349: 2345: 2344: 2341: 2330: 2327: 2326: 2306: 2305: 2296: 2292: 2283: 2279: 2278: 2272: 2268: 2266: 2264: 2255: 2251: 2242: 2238: 2237: 2231: 2227: 2225: 2223: 2211: 2210: 2201: 2197: 2188: 2184: 2183: 2177: 2173: 2171: 2169: 2160: 2156: 2147: 2143: 2142: 2136: 2132: 2130: 2128: 2116: 2115: 2104: 2090: 2088: 2085: 2084: 2066: 2058: 2050: 2046: 2042: 2040: 2035: 2033: 2028: 2026: 2021: 2019: 2014: 1997: 1996: 1990: 1986: 1984: 1978: 1974: 1972: 1960: 1959: 1953: 1949: 1947: 1941: 1937: 1935: 1923: 1922: 1911: 1897: 1895: 1892: 1891: 1887:can be written 1884: 1880: 1869: 1862: 1856:equals zero or 1855: 1848: 1842: 1835: 1826: 1794: 1790: 1784: 1780: 1778: 1770: 1766: 1760: 1756: 1754: 1752: 1740: 1736: 1731: 1725: 1721: 1720: 1713: 1709: 1704: 1698: 1694: 1693: 1691: 1676: 1672: 1658: 1652: 1648: 1647: 1637: 1633: 1619: 1613: 1609: 1608: 1606: 1595: 1592: 1591: 1586: 1579: 1569:, or any other 1558: 1524: 1520: 1518: 1515: 1514: 1497: 1493: 1491: 1488: 1487: 1459: 1455: 1446: 1442: 1440: 1438: 1435: 1434: 1417: 1416: 1411: 1406: 1401: 1398: 1397: 1392: 1387: 1382: 1379: 1378: 1373: 1371: 1366: 1361: 1359: 1356: 1355: 1331: 1327: 1325: 1322: 1321: 1304: 1300: 1298: 1295: 1294: 1287:random sampling 1255: 1252: 1251: 1229: 1226: 1225: 1208: 1204: 1195: 1191: 1189: 1186: 1185: 1168: 1164: 1155: 1151: 1149: 1146: 1145: 1140:like this, the 1103: 1089: 1085: 1076: 1072: 1070: 1058: 1054: 1049: 1043: 1039: 1038: 1031: 1027: 1022: 1016: 1012: 1011: 1009: 1001: 999: 996: 995: 959: 947: 943: 938: 932: 928: 926: 923: 922: 890: 878: 874: 869: 863: 859: 857: 854: 853: 815: 801: 797: 788: 784: 782: 770: 766: 761: 755: 751: 750: 743: 739: 734: 728: 724: 723: 721: 706: 702: 693: 689: 681: 675: 671: 670: 660: 656: 647: 643: 635: 629: 625: 624: 622: 614: 612: 609: 608: 574: 562: 558: 553: 547: 543: 541: 538: 537: 512: 500: 496: 491: 485: 481: 479: 476: 475: 454: 453: 448: 443: 438: 435: 434: 429: 424: 419: 416: 415: 410: 408: 403: 398: 396: 393: 392: 362: 358: 356: 353: 352: 329: 325: 323: 320: 319: 293: 289: 287: 284: 283: 260: 256: 254: 251: 250: 227: 223: 221: 218: 217: 191: 187: 185: 182: 181: 178: 162: 157: 75: 64: 58: 55: 45:Please help to 44: 28: 24: 17: 12: 11: 5: 13487: 13477: 13476: 13471: 13466: 13461: 13446: 13445: 13433: 13410: 13409: 13407: 13406: 13394: 13382: 13368: 13355: 13352: 13351: 13348: 13347: 13344: 13343: 13341: 13340: 13335: 13330: 13325: 13320: 13314: 13312: 13306: 13305: 13303: 13302: 13297: 13292: 13287: 13282: 13277: 13272: 13267: 13262: 13257: 13251: 13249: 13243: 13242: 13240: 13239: 13234: 13229: 13220: 13215: 13210: 13204: 13202: 13196: 13195: 13193: 13192: 13187: 13182: 13173: 13171:Bioinformatics 13167: 13165: 13155: 13154: 13142: 13141: 13138: 13137: 13134: 13133: 13130: 13129: 13127: 13126: 13120: 13118: 13114: 13113: 13111: 13110: 13104: 13102: 13096: 13095: 13093: 13092: 13087: 13082: 13077: 13071: 13069: 13060: 13054: 13053: 13050: 13049: 13047: 13046: 13041: 13036: 13031: 13026: 13020: 13018: 13012: 13011: 13009: 13008: 13003: 12998: 12990: 12985: 12980: 12979: 12978: 12976:partial (PACF) 12967: 12965: 12959: 12958: 12956: 12955: 12950: 12945: 12937: 12932: 12926: 12924: 12923:Specific tests 12920: 12919: 12917: 12916: 12911: 12906: 12901: 12896: 12891: 12886: 12881: 12875: 12873: 12866: 12860: 12859: 12857: 12856: 12855: 12854: 12853: 12852: 12837: 12836: 12835: 12825: 12823:Classification 12820: 12815: 12810: 12805: 12800: 12795: 12789: 12787: 12781: 12780: 12778: 12777: 12772: 12770:McNemar's test 12767: 12762: 12757: 12752: 12746: 12744: 12734: 12733: 12709: 12708: 12705: 12704: 12701: 12700: 12698: 12697: 12692: 12687: 12682: 12676: 12674: 12668: 12667: 12665: 12664: 12648: 12642: 12640: 12634: 12633: 12631: 12630: 12625: 12620: 12615: 12610: 12608:Semiparametric 12605: 12600: 12594: 12592: 12588: 12587: 12585: 12584: 12579: 12574: 12569: 12563: 12561: 12555: 12554: 12552: 12551: 12546: 12541: 12536: 12531: 12525: 12523: 12517: 12516: 12514: 12513: 12508: 12503: 12498: 12492: 12490: 12480: 12479: 12476: 12475: 12470: 12464: 12456: 12455: 12452: 12451: 12448: 12447: 12445: 12444: 12443: 12442: 12432: 12427: 12422: 12421: 12420: 12415: 12404: 12402: 12396: 12395: 12392: 12391: 12389: 12388: 12383: 12382: 12381: 12373: 12365: 12349: 12346:(Mann–Whitney) 12341: 12340: 12339: 12326: 12325: 12324: 12313: 12311: 12305: 12304: 12302: 12301: 12300: 12299: 12294: 12289: 12279: 12274: 12271:(Shapiro–Wilk) 12266: 12261: 12256: 12251: 12246: 12238: 12232: 12230: 12224: 12223: 12221: 12220: 12212: 12203: 12191: 12185: 12183:Specific tests 12179: 12178: 12175: 12174: 12172: 12171: 12166: 12161: 12155: 12153: 12147: 12146: 12144: 12143: 12138: 12137: 12136: 12126: 12125: 12124: 12114: 12108: 12106: 12100: 12099: 12097: 12096: 12095: 12094: 12089: 12079: 12074: 12069: 12064: 12059: 12053: 12051: 12045: 12044: 12042: 12041: 12036: 12035: 12034: 12029: 12028: 12027: 12022: 12007: 12006: 12005: 12000: 11995: 11990: 11979: 11977: 11968: 11962: 11961: 11959: 11958: 11953: 11948: 11947: 11946: 11936: 11931: 11930: 11929: 11919: 11918: 11917: 11912: 11907: 11897: 11892: 11887: 11886: 11885: 11880: 11875: 11859: 11858: 11857: 11852: 11847: 11837: 11836: 11835: 11830: 11820: 11819: 11818: 11808: 11807: 11806: 11796: 11791: 11786: 11780: 11778: 11768: 11767: 11755: 11754: 11751: 11750: 11747: 11746: 11744: 11743: 11738: 11733: 11728: 11722: 11720: 11714: 11713: 11711: 11710: 11705: 11700: 11694: 11692: 11688: 11687: 11685: 11684: 11679: 11674: 11669: 11664: 11659: 11654: 11648: 11646: 11640: 11639: 11637: 11636: 11634:Standard error 11631: 11626: 11621: 11620: 11619: 11614: 11603: 11601: 11595: 11594: 11592: 11591: 11586: 11581: 11576: 11571: 11566: 11564:Optimal design 11561: 11556: 11550: 11548: 11538: 11537: 11525: 11524: 11521: 11520: 11517: 11516: 11514: 11513: 11508: 11503: 11498: 11493: 11488: 11483: 11478: 11473: 11468: 11463: 11458: 11453: 11448: 11443: 11437: 11435: 11429: 11428: 11426: 11425: 11420: 11419: 11418: 11413: 11403: 11398: 11392: 11390: 11384: 11383: 11381: 11380: 11375: 11370: 11364: 11362: 11361:Summary tables 11358: 11357: 11355: 11354: 11348: 11346: 11340: 11339: 11336: 11335: 11333: 11332: 11331: 11330: 11325: 11320: 11310: 11304: 11302: 11296: 11295: 11293: 11292: 11287: 11282: 11277: 11272: 11267: 11262: 11256: 11254: 11248: 11247: 11245: 11244: 11239: 11234: 11233: 11232: 11227: 11222: 11217: 11212: 11207: 11202: 11197: 11195:Contraharmonic 11192: 11187: 11176: 11174: 11165: 11155: 11154: 11142: 11141: 11139: 11138: 11133: 11127: 11124: 11123: 11116: 11115: 11108: 11101: 11093: 11084: 11083: 11081: 11080: 11077:List of topics 11073: 11066: 11058: 11055: 11054: 11052: 11051: 11046: 11041: 11036: 11031: 11029:Selection bias 11025: 11023: 11019: 11018: 11016: 11015: 11010: 11005: 11000: 10995: 10989: 10987: 10981: 10980: 10978: 10977: 10972: 10967: 10962: 10957: 10952: 10950:Animal testing 10947: 10942: 10936: 10934: 10930: 10929: 10926: 10925: 10902:Mortality rate 10888: 10886: 10880: 10879: 10862: 10860: 10854: 10853: 10824: 10822: 10816: 10815: 10794: 10792: 10783: 10777: 10776: 10774: 10773: 10768: 10763: 10758: 10748: 10747: 10746: 10741: 10731: 10717: 10715: 10703: 10702: 10700: 10699: 10698: 10697: 10695:Platform trial 10687: 10686: 10685: 10680: 10675: 10664: 10662: 10650: 10649: 10647: 10646: 10641: 10636: 10631: 10626: 10621: 10620: 10619: 10614: 10607:Clinical trial 10603: 10601: 10597: 10596: 10585: 10584: 10577: 10570: 10562: 10556: 10555: 10550: 10545: 10538: 10537:External links 10535: 10533: 10532: 10514:(1): 109–114. 10499: 10497: 10494: 10491: 10490: 10436: 10417:(4): 299–307. 10411:Am J Epidemiol 10397: 10379: 10357: 10339: 10332: 10314: 10302: 10253: 10226:(4): 685–688. 10210: 10175: 10123: 10105: 10044: 10001: 9966: 9939:(19): 1690–1. 9920: 9885: 9836: 9807:(4): 533–536. 9784: 9753: 9724:(3): 227–229. 9703: 9702: 9700: 9697: 9695: 9692: 9691: 9690: 9685: 9680: 9675: 9670: 9665: 9660: 9653: 9650: 9631: 9628: 9625: 9622: 9619: 9616: 9613: 9607: 9604: 9601: 9597: 9592: 9586: 9583: 9580: 9576: 9571: 9549: 9529: 9516:method, a 95% 9498: 9495: 9492: 9468: 9465: 9460: 9456: 9432: 9429: 9423: 9420: 9397: 9394: 9388: 9385: 9359: 9356: 9353: 9349: 9345: 9342: 9336: 9333: 9314: 9313: 9310: 9307: 9303: 9302: 9299: 9296: 9292: 9291: 9288: 9285: 9274: 9271: 9251: 9243: 9240: 9233: 9230: 9223: 9220: 9214: 9211: 9204: 9201: 9192: 9184: 9181: 9174: 9171: 9164: 9161: 9155: 9152: 9145: 9142: 9133: 9111: 9091: 9088: 9085: 9082: 9079: 9075: 9071: 9068: 9065: 9045: 9023: 9020: 9013: 9010: 8984: 8981: 8974: 8971: 8947: 8929:McNemar's test 8916: 8913: 8910: 8890: 8887: 8884: 8861: 8858: 8855: 8852: 8849: 8846: 8843: 8839: 8835: 8832: 8829: 8826: 8823: 8820: 8817: 8790: 8787: 8757: 8754: 8724: 8721: 8695: 8692: 8665: 8645: 8618: 8615: 8587: 8583: 8578: 8572: 8568: 8564: 8558: 8555: 8530: 8525: 8521: 8517: 8512: 8508: 8504: 8499: 8495: 8491: 8485: 8482: 8476: 8471: 8467: 8441: 8438: 8430: 8426: 8405: 8402: 8399: 8393: 8390: 8384: 8381: 8376: 8372: 8368: 8363: 8359: 8355: 8333: 8330: 8327: 8321: 8318: 8312: 8308: 8301: 8298: 8292: 8289: 8284: 8280: 8276: 8271: 8267: 8263: 8259: 8253: 8249: 8245: 8239: 8236: 8211: 8187: 8184: 8181: 8176: 8172: 8168: 8163: 8159: 8155: 8129: 8125: 8102: 8099: 8096: 8093: 8090: 8086: 8082: 8079: 8076: 8071: 8067: 8061: 8057: 8053: 8048: 8044: 8038: 8034: 8030: 8026: 8022: 8017: 8013: 8007: 8003: 7999: 7996: 7993: 7967: 7945: 7940: 7936: 7930: 7926: 7922: 7918: 7912: 7908: 7902: 7898: 7894: 7891: 7886: 7882: 7877: 7871: 7867: 7863: 7859: 7855: 7850: 7846: 7841: 7835: 7831: 7827: 7824: 7821: 7797: 7793: 7787: 7783: 7760: 7756: 7750: 7746: 7720: 7716: 7712: 7709: 7706: 7701: 7697: 7672: 7668: 7664: 7661: 7658: 7653: 7649: 7624: 7620: 7595: 7591: 7555: 7551: 7528: 7524: 7501: 7497: 7474: 7470: 7456: 7455: 7442: 7438: 7427: 7414: 7410: 7399: 7398:Case unexposed 7395: 7394: 7381: 7377: 7366: 7353: 7349: 7338: 7334: 7333: 7330: 7327: 7320: 7317: 7303: 7300: 7292:Edwards (1963) 7263: 7260: 7257: 7256: 7253: 7234: 7231: 7225: 7224: 7221: 7207: 7201: 7195: 7194: 7191: 7173: 7170: 7164: 7163: 7160: 7151: 7148: 7141: 7140: 7137: 7126: 7123: 7117: 7116: 7113: 7104: 7101: 7095: 7094: 7091: 7088: 7083: 7075: 7074: 7071: 7070:= 0.4, or 40% 7055: 7054:= 0.1, or 10% 7039: 7035: 7034: 7031: 7017: 7003: 6999: 6998: 6995: 6989: 6983: 6979: 6978: 6975: 6969: 6963: 6959: 6958: 6955: 6949: 6946: 6936: 6933: 6930: 6929: 6926: 6923: 6920: 6917: 6914: 6911: 6908: 6905: 6898: 6897: 6894: 6891: 6888: 6885: 6882: 6879: 6876: 6873: 6866: 6865: 6859: 6853: 6847: 6841: 6835: 6829: 6823: 6816: 6815: 6805: 6795: 6785: 6775: 6757:The following 6753: 6752: 6749: 6746: 6743: 6740: 6737: 6734: 6731: 6728: 6721: 6720: 6717: 6714: 6711: 6708: 6705: 6702: 6699: 6696: 6689: 6688: 6682: 6676: 6670: 6664: 6658: 6652: 6646: 6639: 6638: 6628: 6618: 6608: 6598: 6581: 6578: 6564: 6561: 6547: 6541: 6534: 6528: 6518: 6515: 6513: 6510: 6496: 6493: 6471: 6468: 6447: 6441: 6440: 6426: 6418: 6413: 6409: 6405: 6402: 6397: 6393: 6389: 6386: 6377: 6333: 6330: 6305: 6302: 6298: 6297: 6290: 6283: = 1 6276: = 0 6244: 6238: 6231: 6225: 6215: 6214: 6194: 6190: 6186: 6181: 6177: 6169: 6165: 6161: 6158: 6155: 6152: 6149: 6143: 6136: 6132: 6128: 6123: 6119: 6111: 6107: 6103: 6100: 6097: 6094: 6091: 6085: 6083: 6080: 6077: 6074: 6073: 6065: 6061: 6057: 6052: 6048: 6040: 6036: 6032: 6026: 6019: 6015: 6011: 6006: 6002: 5994: 5990: 5986: 5980: 5978: 5975: 5972: 5969: 5968: 5965: 5962: 5959: 5956: 5954: 5951: 5948: 5945: 5943: 5926:1 âˆ’  5922: = 0 5911: = 1 5881: 5878: 5871: 5866: 5849: 5846: 5840: 5834: 5811: 5806: 5799: 5796: 5789: 5786: 5783: 5763: 5758: 5751: 5748: 5741: 5738: 5735: 5724: 5723: 5712: 5706: 5701: 5697: 5693: 5690: 5687: 5682: 5678: 5674: 5671: 5668: 5665: 5662: 5659: 5656: 5653: 5650: 5647: 5643: 5639: 5634: 5630: 5626: 5623: 5620: 5615: 5611: 5607: 5604: 5601: 5598: 5595: 5592: 5589: 5586: 5583: 5580: 5575: 5570: 5566: 5562: 5559: 5556: 5551: 5547: 5543: 5540: 5537: 5534: 5531: 5528: 5525: 5522: 5519: 5516: 5512: 5508: 5503: 5499: 5495: 5492: 5489: 5484: 5480: 5476: 5473: 5470: 5467: 5464: 5461: 5458: 5455: 5452: 5449: 5443: 5440: 5435: 5431: 5427: 5424: 5421: 5418: 5411: 5407: 5402: 5372: 5365: 5362: 5345: 5338: 5323: 5317: 5299: 5296: 5220: 5219: 5199: 5195: 5191: 5185: 5177: 5173: 5169: 5163: 5155: 5151: 5147: 5141: 5133: 5129: 5125: 5117: 5112: 5109: 5092:standard error 5088: 5087: 5075: 5072: 5067: 5063: 5058: 5055: 5052: 5049: 5046: 5043: 5040: 5037: 5032: 5024: 5018: 5000: 4999: 4985: 4976: 4972: 4966: 4962: 4954: 4950: 4944: 4940: 4932: 4928: 4925: 4922: 4918: 4909: 4902: 4899: 4890: 4883: 4880: 4869: 4862: 4859: 4850: 4843: 4840: 4829: 4825: 4822: 4819: 4816: 4799: 4792: 4785: 4778: 4759: 4750: 4734: 4733: 4716: 4709: 4706: 4699: 4695: 4688: 4685: 4678: 4676: 4673: 4670: 4667: 4666: 4661: 4654: 4651: 4644: 4640: 4633: 4630: 4623: 4621: 4618: 4615: 4612: 4611: 4608: 4605: 4602: 4599: 4597: 4594: 4591: 4588: 4586: 4572: 4571: 4554: 4550: 4546: 4542: 4538: 4534: 4532: 4529: 4526: 4523: 4522: 4517: 4513: 4509: 4505: 4501: 4497: 4495: 4492: 4489: 4486: 4485: 4482: 4479: 4476: 4473: 4471: 4468: 4465: 4462: 4460: 4443: 4442: 4430: 4426: 4421: 4417: 4413: 4410: 4407: 4404: 4401: 4396: 4392: 4388: 4385: 4382: 4379: 4374: 4367: 4363: 4359: 4356: 4353: 4350: 4347: 4342: 4338: 4334: 4331: 4328: 4325: 4321: 4313: 4309: 4303: 4299: 4291: 4287: 4281: 4277: 4270: 4266: 4263: 4231: 4228: 4207: 4206: 4195: 4192: 4187: 4184: 4179: 4172: 4169: 4166: 4159: 4156: 4153: 4146: 4140: 4136: 4132: 4127: 4123: 4119: 4101: 4100: 4089: 4086: 4079: 4076: 4073: 4066: 4063: 4060: 4053: 4049: 4046: 4031: 4030: 4015: 4012: 4010: 4007: 4005: 4002: 3999: 3996: 3995: 3992: 3989: 3987: 3984: 3982: 3979: 3976: 3973: 3972: 3969: 3966: 3963: 3960: 3958: 3955: 3952: 3949: 3947: 3887: 3884: 3878: 3866: 3860: 3853: 3846: = 1 3839: 3838: 3827: 3820: 3817: 3813: 3807: 3804: 3800: 3796: 3793: 3790: 3787: 3784: 3781: 3778: 3775: 3770: 3766: 3762: 3759: 3756: 3753: 3750: 3747: 3742: 3739: 3735: 3731: 3726: 3723: 3719: 3715: 3712: 3709: 3706: 3701: 3698: 3682: 3675: 3668: 3661: 3654: 3647: 3640: 3639: 3625: 3622: 3619: 3616: 3613: 3610: 3605: 3602: 3599: 3596: 3593: 3590: 3587: 3584: 3579: 3576: 3572: 3568: 3563: 3560: 3556: 3552: 3549: 3546: 3540: 3535: 3531: 3510: 3503: 3486: 3479: 3463: 3460: 3444: 3443: 3428: 3423: 3419: 3415: 3412: 3409: 3406: 3401: 3397: 3393: 3390: 3387: 3384: 3380: 3376: 3372: 3367: 3363: 3359: 3356: 3353: 3350: 3348: 3345: 3342: 3339: 3338: 3335: 3330: 3326: 3322: 3319: 3316: 3311: 3307: 3303: 3299: 3295: 3289: 3285: 3281: 3279: 3276: 3273: 3270: 3269: 3266: 3263: 3260: 3257: 3255: 3252: 3249: 3246: 3244: 3222: =  3217: 3202: =  3197: 3181: 3178: 3166: 3165: 3154: 3145: 3141: 3135: 3131: 3123: 3119: 3113: 3109: 3101: 3094: 3089: 3085: 3081: 3076: 3072: 3068: 3064: 3058: 3054: 3048: 3043: 3039: 3035: 3030: 3026: 3022: 3018: 3012: 3008: 2998: 2989: 2984: 2980: 2976: 2971: 2967: 2963: 2959: 2953: 2949: 2943: 2938: 2934: 2930: 2925: 2921: 2917: 2913: 2907: 2903: 2884: 2883: 2863: 2859: 2855: 2850: 2846: 2839: 2835: 2829: 2822: 2818: 2814: 2809: 2805: 2798: 2794: 2788: 2786: 2783: 2780: 2777: 2776: 2768: 2764: 2760: 2755: 2751: 2744: 2740: 2734: 2727: 2723: 2719: 2714: 2710: 2703: 2699: 2693: 2691: 2688: 2685: 2682: 2681: 2678: 2675: 2672: 2669: 2667: 2664: 2661: 2658: 2656: 2637: 2634: 2606: 2605: 2589: 2585: 2579: 2575: 2567: 2563: 2557: 2553: 2546: 2539: 2534: 2530: 2526: 2521: 2517: 2513: 2509: 2503: 2499: 2493: 2488: 2484: 2480: 2475: 2471: 2467: 2463: 2457: 2453: 2443: 2434: 2429: 2425: 2421: 2416: 2412: 2408: 2404: 2398: 2394: 2388: 2383: 2379: 2375: 2370: 2366: 2362: 2358: 2352: 2348: 2340: 2337: 2334: 2320: 2319: 2299: 2295: 2291: 2286: 2282: 2275: 2271: 2265: 2258: 2254: 2250: 2245: 2241: 2234: 2230: 2224: 2222: 2219: 2216: 2213: 2212: 2204: 2200: 2196: 2191: 2187: 2180: 2176: 2170: 2163: 2159: 2155: 2150: 2146: 2139: 2135: 2129: 2127: 2124: 2121: 2118: 2117: 2114: 2111: 2108: 2105: 2103: 2100: 2097: 2094: 2092: 2038: 2031: 2024: 2017: 2011: 2010: 1993: 1989: 1985: 1981: 1977: 1973: 1971: 1968: 1965: 1962: 1961: 1956: 1952: 1948: 1944: 1940: 1936: 1934: 1931: 1928: 1925: 1924: 1921: 1918: 1915: 1912: 1910: 1907: 1904: 1901: 1899: 1875:of two binary 1868: 1865: 1860: 1853: 1846: 1840: 1831: 1824: 1818: 1817: 1806: 1797: 1793: 1787: 1783: 1773: 1769: 1763: 1759: 1751: 1743: 1739: 1734: 1728: 1724: 1716: 1712: 1707: 1701: 1697: 1690: 1684: 1679: 1675: 1671: 1668: 1665: 1661: 1655: 1651: 1645: 1640: 1636: 1632: 1629: 1626: 1622: 1616: 1612: 1605: 1602: 1599: 1584: 1577: 1557: 1554: 1527: 1523: 1500: 1496: 1475: 1472: 1466: 1462: 1458: 1453: 1449: 1445: 1431: 1430: 1415: 1412: 1410: 1407: 1400: 1399: 1396: 1393: 1391: 1388: 1381: 1380: 1372: 1365: 1363: 1334: 1330: 1307: 1303: 1268: 1265: 1262: 1259: 1239: 1236: 1233: 1211: 1207: 1203: 1198: 1194: 1171: 1167: 1163: 1158: 1154: 1134: 1133: 1122: 1118: 1115: 1110: 1107: 1102: 1096: 1092: 1088: 1083: 1079: 1075: 1069: 1061: 1057: 1052: 1046: 1042: 1034: 1030: 1025: 1019: 1015: 1008: 976: 972: 969: 966: 962: 958: 955: 950: 946: 941: 935: 931: 906: 903: 900: 897: 893: 889: 886: 881: 877: 872: 866: 862: 846: 845: 834: 830: 827: 822: 819: 814: 808: 804: 800: 795: 791: 787: 781: 773: 769: 764: 758: 754: 746: 742: 737: 731: 727: 720: 714: 709: 705: 701: 696: 692: 688: 684: 678: 674: 668: 663: 659: 655: 650: 646: 642: 638: 632: 628: 621: 587: 584: 581: 577: 573: 570: 565: 561: 556: 550: 546: 525: 522: 519: 515: 511: 508: 503: 499: 494: 488: 484: 468: 467: 452: 449: 447: 444: 437: 436: 433: 430: 428: 425: 418: 417: 409: 402: 400: 373: 370: 365: 361: 340: 337: 332: 328: 307: 304: 301: 296: 292: 271: 268: 263: 259: 238: 235: 230: 226: 205: 202: 199: 194: 190: 177: 171: 161: 158: 156: 153: 149:logistic model 77: 76: 31: 29: 22: 15: 9: 6: 4: 3: 2: 13486: 13475: 13472: 13470: 13467: 13465: 13462: 13460: 13457: 13456: 13454: 13444: 13439: 13434: 13432: 13422: 13421: 13418: 13405: 13404: 13395: 13393: 13392: 13383: 13381: 13380: 13375: 13369: 13367: 13366: 13357: 13356: 13353: 13339: 13336: 13334: 13333:Geostatistics 13331: 13329: 13326: 13324: 13321: 13319: 13316: 13315: 13313: 13311: 13307: 13301: 13300:Psychometrics 13298: 13296: 13293: 13291: 13288: 13286: 13283: 13281: 13278: 13276: 13273: 13271: 13268: 13266: 13263: 13261: 13258: 13256: 13253: 13252: 13250: 13248: 13244: 13238: 13235: 13233: 13230: 13228: 13224: 13221: 13219: 13216: 13214: 13211: 13209: 13206: 13205: 13203: 13201: 13197: 13191: 13188: 13186: 13183: 13181: 13177: 13174: 13172: 13169: 13168: 13166: 13164: 13163:Biostatistics 13160: 13156: 13152: 13147: 13143: 13125: 13124:Log-rank test 13122: 13121: 13119: 13115: 13109: 13106: 13105: 13103: 13101: 13097: 13091: 13088: 13086: 13083: 13081: 13078: 13076: 13073: 13072: 13070: 13068: 13064: 13061: 13059: 13055: 13045: 13042: 13040: 13037: 13035: 13032: 13030: 13027: 13025: 13022: 13021: 13019: 13017: 13013: 13007: 13004: 13002: 12999: 12997: 12995:(Box–Jenkins) 12991: 12989: 12986: 12984: 12981: 12977: 12974: 12973: 12972: 12969: 12968: 12966: 12964: 12960: 12954: 12951: 12949: 12948:Durbin–Watson 12946: 12944: 12938: 12936: 12933: 12931: 12930:Dickey–Fuller 12928: 12927: 12925: 12921: 12915: 12912: 12910: 12907: 12905: 12904:Cointegration 12902: 12900: 12897: 12895: 12892: 12890: 12887: 12885: 12882: 12880: 12879:Decomposition 12877: 12876: 12874: 12870: 12867: 12865: 12861: 12851: 12848: 12847: 12846: 12843: 12842: 12841: 12838: 12834: 12831: 12830: 12829: 12826: 12824: 12821: 12819: 12816: 12814: 12811: 12809: 12806: 12804: 12801: 12799: 12796: 12794: 12791: 12790: 12788: 12786: 12782: 12776: 12773: 12771: 12768: 12766: 12763: 12761: 12758: 12756: 12753: 12751: 12750:Cohen's kappa 12748: 12747: 12745: 12743: 12739: 12735: 12731: 12727: 12723: 12719: 12714: 12710: 12696: 12693: 12691: 12688: 12686: 12683: 12681: 12678: 12677: 12675: 12673: 12669: 12663: 12659: 12655: 12649: 12647: 12644: 12643: 12641: 12639: 12635: 12629: 12626: 12624: 12621: 12619: 12616: 12614: 12611: 12609: 12606: 12604: 12603:Nonparametric 12601: 12599: 12596: 12595: 12593: 12589: 12583: 12580: 12578: 12575: 12573: 12570: 12568: 12565: 12564: 12562: 12560: 12556: 12550: 12547: 12545: 12542: 12540: 12537: 12535: 12532: 12530: 12527: 12526: 12524: 12522: 12518: 12512: 12509: 12507: 12504: 12502: 12499: 12497: 12494: 12493: 12491: 12489: 12485: 12481: 12474: 12471: 12469: 12466: 12465: 12461: 12457: 12441: 12438: 12437: 12436: 12433: 12431: 12428: 12426: 12423: 12419: 12416: 12414: 12411: 12410: 12409: 12406: 12405: 12403: 12401: 12397: 12387: 12384: 12380: 12374: 12372: 12366: 12364: 12358: 12357: 12356: 12353: 12352:Nonparametric 12350: 12348: 12342: 12338: 12335: 12334: 12333: 12327: 12323: 12322:Sample median 12320: 12319: 12318: 12315: 12314: 12312: 12310: 12306: 12298: 12295: 12293: 12290: 12288: 12285: 12284: 12283: 12280: 12278: 12275: 12273: 12267: 12265: 12262: 12260: 12257: 12255: 12252: 12250: 12247: 12245: 12243: 12239: 12237: 12234: 12233: 12231: 12229: 12225: 12219: 12217: 12213: 12211: 12209: 12204: 12202: 12197: 12193: 12192: 12189: 12186: 12184: 12180: 12170: 12167: 12165: 12162: 12160: 12157: 12156: 12154: 12152: 12148: 12142: 12139: 12135: 12132: 12131: 12130: 12127: 12123: 12120: 12119: 12118: 12115: 12113: 12110: 12109: 12107: 12105: 12101: 12093: 12090: 12088: 12085: 12084: 12083: 12080: 12078: 12075: 12073: 12070: 12068: 12065: 12063: 12060: 12058: 12055: 12054: 12052: 12050: 12046: 12040: 12037: 12033: 12030: 12026: 12023: 12021: 12018: 12017: 12016: 12013: 12012: 12011: 12008: 12004: 12001: 11999: 11996: 11994: 11991: 11989: 11986: 11985: 11984: 11981: 11980: 11978: 11976: 11972: 11969: 11967: 11963: 11957: 11954: 11952: 11949: 11945: 11942: 11941: 11940: 11937: 11935: 11932: 11928: 11927:loss function 11925: 11924: 11923: 11920: 11916: 11913: 11911: 11908: 11906: 11903: 11902: 11901: 11898: 11896: 11893: 11891: 11888: 11884: 11881: 11879: 11876: 11874: 11868: 11865: 11864: 11863: 11860: 11856: 11853: 11851: 11848: 11846: 11843: 11842: 11841: 11838: 11834: 11831: 11829: 11826: 11825: 11824: 11821: 11817: 11814: 11813: 11812: 11809: 11805: 11802: 11801: 11800: 11797: 11795: 11792: 11790: 11787: 11785: 11782: 11781: 11779: 11777: 11773: 11769: 11765: 11760: 11756: 11742: 11739: 11737: 11734: 11732: 11729: 11727: 11724: 11723: 11721: 11719: 11715: 11709: 11706: 11704: 11701: 11699: 11696: 11695: 11693: 11689: 11683: 11680: 11678: 11675: 11673: 11670: 11668: 11665: 11663: 11660: 11658: 11655: 11653: 11650: 11649: 11647: 11645: 11641: 11635: 11632: 11630: 11629:Questionnaire 11627: 11625: 11622: 11618: 11615: 11613: 11610: 11609: 11608: 11605: 11604: 11602: 11600: 11596: 11590: 11587: 11585: 11582: 11580: 11577: 11575: 11572: 11570: 11567: 11565: 11562: 11560: 11557: 11555: 11552: 11551: 11549: 11547: 11543: 11539: 11535: 11530: 11526: 11512: 11509: 11507: 11504: 11502: 11499: 11497: 11494: 11492: 11489: 11487: 11484: 11482: 11479: 11477: 11474: 11472: 11469: 11467: 11464: 11462: 11459: 11457: 11456:Control chart 11454: 11452: 11449: 11447: 11444: 11442: 11439: 11438: 11436: 11434: 11430: 11424: 11421: 11417: 11414: 11412: 11409: 11408: 11407: 11404: 11402: 11399: 11397: 11394: 11393: 11391: 11389: 11385: 11379: 11376: 11374: 11371: 11369: 11366: 11365: 11363: 11359: 11353: 11350: 11349: 11347: 11345: 11341: 11329: 11326: 11324: 11321: 11319: 11316: 11315: 11314: 11311: 11309: 11306: 11305: 11303: 11301: 11297: 11291: 11288: 11286: 11283: 11281: 11278: 11276: 11273: 11271: 11268: 11266: 11263: 11261: 11258: 11257: 11255: 11253: 11249: 11243: 11240: 11238: 11235: 11231: 11228: 11226: 11223: 11221: 11218: 11216: 11213: 11211: 11208: 11206: 11203: 11201: 11198: 11196: 11193: 11191: 11188: 11186: 11183: 11182: 11181: 11178: 11177: 11175: 11173: 11169: 11166: 11164: 11160: 11156: 11152: 11147: 11143: 11137: 11134: 11132: 11129: 11128: 11125: 11121: 11114: 11109: 11107: 11102: 11100: 11095: 11094: 11091: 11079: 11078: 11074: 11072: 11071: 11067: 11065: 11064: 11060: 11059: 11056: 11050: 11047: 11045: 11042: 11040: 11037: 11035: 11032: 11030: 11027: 11026: 11024: 11020: 11014: 11011: 11009: 11008:Meta-analysis 11006: 11004: 11001: 10999: 10996: 10994: 10991: 10990: 10988: 10986: 10982: 10976: 10975:Vaccine trial 10973: 10971: 10970:Seeding trial 10968: 10966: 10963: 10961: 10958: 10956: 10953: 10951: 10948: 10946: 10943: 10941: 10938: 10937: 10935: 10931: 10923: 10919: 10915: 10911: 10907: 10903: 10899: 10895: 10891: 10887: 10885: 10881: 10877: 10873: 10869: 10865: 10861: 10859: 10855: 10851: 10847: 10843: 10839: 10835: 10831: 10827: 10823: 10821: 10817: 10813: 10809: 10805: 10801: 10797: 10793: 10791: 10787: 10784: 10782: 10778: 10772: 10769: 10767: 10764: 10762: 10759: 10756: 10752: 10749: 10745: 10742: 10740: 10739:Retrospective 10737: 10736: 10735: 10732: 10730: 10726: 10722: 10719: 10718: 10716: 10713: 10708: 10704: 10696: 10693: 10692: 10691: 10688: 10684: 10681: 10679: 10676: 10674: 10671: 10670: 10669: 10666: 10665: 10663: 10660: 10659:EBM I to II-1 10655: 10651: 10645: 10642: 10640: 10637: 10635: 10632: 10630: 10627: 10625: 10622: 10618: 10615: 10613: 10610: 10609: 10608: 10605: 10604: 10602: 10598: 10594: 10590: 10583: 10578: 10576: 10571: 10569: 10564: 10563: 10560: 10554: 10551: 10549: 10546: 10544: 10541: 10540: 10529: 10525: 10521: 10517: 10513: 10509: 10505: 10501: 10500: 10486: 10482: 10477: 10472: 10467: 10462: 10459:(7514): 428. 10458: 10454: 10450: 10443: 10441: 10432: 10428: 10424: 10420: 10416: 10412: 10408: 10401: 10393: 10386: 10384: 10375: 10368: 10366: 10364: 10362: 10353: 10346: 10344: 10335: 10329: 10325: 10318: 10312: 10306: 10298: 10294: 10289: 10284: 10280: 10276: 10272: 10268: 10264: 10257: 10249: 10245: 10241: 10237: 10233: 10229: 10225: 10221: 10214: 10206: 10202: 10198: 10194: 10190: 10186: 10179: 10171: 10167: 10162: 10157: 10153: 10149: 10145: 10141: 10137: 10130: 10128: 10119: 10112: 10110: 10101: 10097: 10093: 10089: 10085: 10081: 10077: 10073: 10069: 10065: 10058: 10051: 10049: 10040: 10036: 10032: 10028: 10024: 10020: 10017:(4): 365–71. 10016: 10012: 10005: 9997: 9993: 9989: 9985: 9981: 9977: 9970: 9962: 9958: 9954: 9950: 9946: 9942: 9938: 9934: 9927: 9925: 9916: 9912: 9908: 9904: 9900: 9896: 9889: 9881: 9877: 9872: 9867: 9863: 9859: 9855: 9851: 9847: 9840: 9832: 9828: 9824: 9820: 9815: 9810: 9806: 9802: 9798: 9791: 9789: 9775:on 2013-10-08 9774: 9770: 9766: 9765: 9757: 9749: 9745: 9740: 9735: 9731: 9727: 9723: 9719: 9715: 9708: 9704: 9689: 9686: 9684: 9681: 9679: 9676: 9674: 9671: 9669: 9666: 9664: 9661: 9659: 9656: 9655: 9649: 9647: 9642: 9626: 9623: 9620: 9614: 9605: 9602: 9599: 9595: 9590: 9584: 9581: 9578: 9574: 9561: 9547: 9527: 9519: 9515: 9510: 9496: 9493: 9490: 9482: 9466: 9463: 9458: 9454: 9446: 9430: 9427: 9418: 9395: 9392: 9383: 9371: 9357: 9354: 9351: 9347: 9343: 9340: 9331: 9320: 9311: 9308: 9305: 9304: 9300: 9297: 9294: 9293: 9289: 9286: 9283: 9282: 9279: 9270: 9268: 9263: 9241: 9238: 9228: 9221: 9218: 9212: 9209: 9199: 9190: 9182: 9179: 9169: 9162: 9159: 9153: 9150: 9140: 9123: 9109: 9086: 9083: 9080: 9073: 9069: 9066: 9063: 9043: 9021: 9018: 9008: 8982: 8979: 8969: 8945: 8937: 8932: 8930: 8914: 8911: 8908: 8888: 8885: 8882: 8873: 8859: 8856: 8850: 8847: 8844: 8837: 8833: 8830: 8827: 8824: 8821: 8818: 8815: 8806: 8785: 8774: 8752: 8741: 8719: 8690: 8679: 8663: 8643: 8635: 8613: 8601: 8585: 8581: 8576: 8570: 8566: 8562: 8553: 8542: 8523: 8519: 8515: 8510: 8506: 8502: 8497: 8493: 8480: 8474: 8469: 8465: 8456: 8436: 8428: 8424: 8400: 8397: 8388: 8374: 8370: 8366: 8361: 8357: 8344: 8328: 8325: 8316: 8306: 8296: 8290: 8282: 8278: 8274: 8269: 8265: 8257: 8251: 8247: 8243: 8234: 8223: 8209: 8201: 8182: 8179: 8174: 8170: 8166: 8161: 8157: 8145: 8127: 8123: 8113: 8097: 8094: 8091: 8084: 8080: 8077: 8069: 8065: 8059: 8055: 8051: 8046: 8042: 8036: 8032: 8024: 8015: 8011: 8005: 8001: 7994: 7991: 7983: 7979: 7965: 7956: 7938: 7934: 7928: 7924: 7916: 7910: 7906: 7900: 7896: 7892: 7884: 7880: 7875: 7869: 7865: 7857: 7848: 7844: 7839: 7833: 7829: 7822: 7819: 7811: 7795: 7791: 7785: 7781: 7758: 7754: 7748: 7744: 7734: 7718: 7714: 7710: 7707: 7704: 7699: 7695: 7686: 7670: 7666: 7662: 7659: 7656: 7651: 7647: 7638: 7622: 7618: 7609: 7593: 7589: 7580: 7578: 7574: 7569: 7553: 7549: 7526: 7522: 7499: 7495: 7472: 7468: 7440: 7436: 7428: 7412: 7408: 7400: 7397: 7396: 7379: 7375: 7367: 7351: 7347: 7339: 7336: 7335: 7331: 7328: 7325: 7324: 7316: 7314: 7309: 7299: 7297: 7293: 7289: 7288: 7282: 7281: 7275: 7269: 7254: 7251: 7247: 7243: 7239: 7235: 7232: 7230: 7227: 7226: 7222: 7220: 7216: 7212: 7208: 7202: 7200: 7197: 7196: 7193:0.75, or 75% 7192: 7190: 7186: 7182: 7178: 7174: 7171: 7169: 7166: 7165: 7161: 7159: 7155: 7152: 7149: 7147:(risk ratio) 7146: 7145:Relative risk 7143: 7142: 7138: 7135: 7131: 7127: 7124: 7122: 7119: 7118: 7114: 7112: 7108: 7105: 7102: 7100: 7097: 7096: 7092: 7089: 7087: 7084: 7081: 7080: 7069: 7065: 7061: 7060: 7056: 7053: 7049: 7045: 7044: 7040: 7037: 7036: 7032: 7029: 7025: 7021: 7018: 7015: 7011: 7007: 7004: 7001: 7000: 6996: 6993: 6990: 6987: 6984: 6981: 6980: 6976: 6973: 6970: 6967: 6964: 6961: 6960: 6956: 6953: 6952:Control group 6950: 6947: 6944: 6943: 6927: 6924: 6921: 6918: 6915: 6912: 6909: 6906: 6903: 6900: 6899: 6895: 6892: 6889: 6886: 6883: 6880: 6877: 6874: 6871: 6868: 6867: 6863: 6860: 6857: 6854: 6851: 6848: 6845: 6842: 6839: 6836: 6833: 6830: 6827: 6824: 6821: 6818: 6817: 6813: 6809: 6803: 6799: 6793: 6789: 6783: 6779: 6773: 6770: 6768: 6764: 6760: 6750: 6747: 6744: 6741: 6738: 6735: 6732: 6729: 6726: 6723: 6722: 6718: 6715: 6712: 6709: 6706: 6703: 6700: 6697: 6694: 6691: 6690: 6686: 6683: 6680: 6677: 6674: 6671: 6668: 6665: 6662: 6659: 6656: 6653: 6650: 6647: 6644: 6641: 6640: 6636: 6632: 6626: 6622: 6616: 6612: 6606: 6602: 6596: 6593: 6591: 6587: 6577: 6575: 6571: 6560: 6558: 6554: 6546: 6540: 6537: /  6533: 6527: 6524: 6509: 6505: 6501: 6492: 6488: 6486: 6482: 6476: 6467: 6464: 6460: 6456: 6453: 6450: 6446: 6416: 6411: 6407: 6400: 6395: 6391: 6387: 6384: 6375: 6372:Relative risk 6363: 6362: 6361: 6358: 6355: 6351: 6350:relative risk 6347: 6338: 6329: 6327: 6324:, such as in 6323: 6319: 6315: 6311: 6301: 6295: 6291: 6288: 6282: 6275: 6270: 6266: 6262: 6261: 6260: 6257: 6255: 6251: 6243: 6237: 6234: /  6230: 6224: 6220: 6192: 6188: 6184: 6179: 6175: 6167: 6163: 6156: 6153: 6150: 6134: 6130: 6126: 6121: 6117: 6109: 6105: 6098: 6095: 6092: 6081: 6078: 6075: 6063: 6059: 6055: 6050: 6046: 6038: 6034: 6030: 6017: 6013: 6009: 6004: 6000: 5992: 5988: 5984: 5976: 5973: 5970: 5963: 5960: 5957: 5952: 5949: 5946: 5934: 5933: 5932: 5929: 5921: 5916: 5910: 5905: 5901: 5897: 5879: 5876: 5869: 5864: 5845: 5843: 5833: 5829: 5825: 5804: 5794: 5784: 5781: 5756: 5746: 5736: 5733: 5710: 5699: 5695: 5691: 5688: 5685: 5680: 5676: 5672: 5669: 5666: 5663: 5660: 5657: 5654: 5651: 5645: 5641: 5632: 5628: 5624: 5621: 5618: 5613: 5609: 5605: 5602: 5599: 5596: 5593: 5590: 5587: 5584: 5578: 5568: 5564: 5560: 5557: 5554: 5549: 5545: 5541: 5538: 5535: 5532: 5529: 5526: 5523: 5520: 5514: 5510: 5501: 5497: 5493: 5490: 5487: 5482: 5478: 5474: 5471: 5468: 5465: 5462: 5459: 5456: 5453: 5447: 5441: 5433: 5429: 5422: 5419: 5416: 5409: 5405: 5400: 5392: 5391: 5390: 5388: 5370: 5360: 5348: 5341: 5334: 5330: 5326: 5316: 5312: 5308: 5304: 5295: 5293: 5289: 5284: 5282: 5278: 5274: 5267: 5262: 5258: 5252: 5246: 5242: 5234: 5229: 5225: 5197: 5193: 5189: 5183: 5175: 5171: 5167: 5161: 5153: 5149: 5145: 5139: 5131: 5127: 5123: 5115: 5097: 5096: 5095: 5093: 5073: 5065: 5061: 5056: 5050: 5047: 5041: 5038: 5022: 5016: 5009: 5008: 5007: 5005: 4983: 4974: 4970: 4964: 4960: 4952: 4948: 4942: 4938: 4930: 4926: 4923: 4920: 4916: 4907: 4897: 4888: 4878: 4867: 4857: 4848: 4838: 4827: 4823: 4820: 4817: 4814: 4806: 4805: 4804: 4798: 4795: +  4791: 4788: +  4784: 4781: +  4777: 4774: =  4773: 4767: 4764: /  4762: 4758: 4755: =  4753: 4746: 4714: 4704: 4693: 4683: 4674: 4671: 4668: 4659: 4649: 4638: 4628: 4619: 4616: 4613: 4606: 4603: 4600: 4595: 4592: 4589: 4577: 4576: 4575: 4552: 4548: 4540: 4536: 4530: 4527: 4524: 4515: 4511: 4503: 4499: 4493: 4490: 4487: 4480: 4477: 4474: 4469: 4466: 4463: 4451: 4450: 4449: 4448: 4428: 4419: 4415: 4408: 4405: 4402: 4394: 4390: 4383: 4380: 4377: 4365: 4361: 4354: 4351: 4348: 4340: 4336: 4329: 4326: 4323: 4319: 4311: 4307: 4301: 4297: 4289: 4285: 4279: 4275: 4268: 4264: 4261: 4253: 4252: 4251: 4249: 4244: 4236: 4227: 4225: 4221: 4217: 4216:probabilities 4213: 4193: 4190: 4185: 4182: 4177: 4170: 4167: 4164: 4157: 4154: 4151: 4144: 4138: 4134: 4130: 4125: 4121: 4117: 4107: 4106: 4105: 4087: 4084: 4077: 4074: 4071: 4064: 4061: 4058: 4051: 4047: 4044: 4036: 4035: 4034: 4013: 4008: 4003: 4000: 3997: 3990: 3985: 3980: 3977: 3974: 3967: 3964: 3961: 3956: 3953: 3950: 3938: 3937: 3936: 3929: 3925: 3921: 3917: 3913: 3909: 3905: 3901: 3897: 3892: 3883: 3877: 3873:Once we have 3871: 3865: 3859: 3856: =  3852: 3845: 3825: 3818: 3815: 3811: 3805: 3802: 3798: 3791: 3788: 3785: 3779: 3776: 3773: 3768: 3757: 3754: 3751: 3740: 3737: 3733: 3729: 3724: 3721: 3717: 3710: 3707: 3699: 3696: 3689: 3688: 3687: 3681: 3678: +  3674: 3671: =  3667: 3660: 3657: +  3653: 3650: =  3646: 3620: 3617: 3614: 3608: 3603: 3600: 3594: 3591: 3588: 3577: 3574: 3570: 3566: 3561: 3558: 3554: 3547: 3544: 3538: 3533: 3529: 3521: 3520: 3519: 3517: 3509: 3506: +  3502: 3498: 3494: 3485: 3482: +  3478: 3474: 3470: 3459: 3457: 3453: 3449: 3421: 3417: 3413: 3410: 3399: 3395: 3391: 3388: 3378: 3374: 3365: 3361: 3357: 3354: 3346: 3343: 3340: 3328: 3324: 3320: 3317: 3309: 3305: 3297: 3293: 3287: 3283: 3277: 3274: 3271: 3264: 3261: 3258: 3253: 3250: 3247: 3235: 3234: 3233: 3232:, as follows 3229: 3225: 3220: 3216: 3209: 3205: 3200: 3196: 3191: 3187: 3177: 3175: 3174:relative risk 3171: 3152: 3143: 3139: 3133: 3129: 3121: 3117: 3111: 3107: 3099: 3087: 3083: 3079: 3074: 3070: 3062: 3056: 3052: 3041: 3037: 3033: 3028: 3024: 3016: 3010: 3006: 2982: 2978: 2974: 2969: 2965: 2957: 2951: 2947: 2936: 2932: 2928: 2923: 2919: 2911: 2905: 2901: 2889: 2888: 2887: 2861: 2857: 2853: 2848: 2844: 2837: 2833: 2820: 2816: 2812: 2807: 2803: 2796: 2792: 2784: 2781: 2778: 2766: 2762: 2758: 2753: 2749: 2742: 2738: 2725: 2721: 2717: 2712: 2708: 2701: 2697: 2689: 2686: 2683: 2676: 2673: 2670: 2665: 2662: 2659: 2647: 2646: 2645: 2643: 2633: 2626: â‰   2614: =  2587: 2583: 2577: 2573: 2565: 2561: 2555: 2551: 2544: 2532: 2528: 2524: 2519: 2515: 2507: 2501: 2497: 2486: 2482: 2478: 2473: 2469: 2461: 2455: 2451: 2427: 2423: 2419: 2414: 2410: 2402: 2396: 2392: 2381: 2377: 2373: 2368: 2364: 2356: 2350: 2346: 2338: 2335: 2332: 2325: 2324: 2323: 2297: 2293: 2289: 2284: 2280: 2273: 2269: 2256: 2252: 2248: 2243: 2239: 2232: 2228: 2220: 2217: 2214: 2202: 2198: 2194: 2189: 2185: 2178: 2174: 2161: 2157: 2153: 2148: 2144: 2137: 2133: 2125: 2122: 2119: 2112: 2109: 2106: 2101: 2098: 2095: 2083: 2082: 2081: 2077: 2073: 2069: 2064: 2056: 1991: 1987: 1979: 1975: 1969: 1966: 1963: 1954: 1950: 1942: 1938: 1932: 1929: 1926: 1919: 1916: 1913: 1908: 1905: 1902: 1890: 1889: 1888: 1878: 1874: 1864: 1863:equals zero. 1859: 1852: 1845: 1839: 1834: 1830: 1823: 1804: 1795: 1791: 1785: 1781: 1771: 1767: 1761: 1757: 1749: 1741: 1737: 1732: 1726: 1722: 1714: 1710: 1705: 1699: 1695: 1688: 1677: 1673: 1669: 1666: 1659: 1653: 1649: 1638: 1634: 1630: 1627: 1620: 1614: 1610: 1603: 1600: 1597: 1590: 1589: 1588: 1583: 1576: 1572: 1568: 1567:control group 1563: 1553: 1551: 1547: 1541: 1525: 1521: 1498: 1494: 1473: 1470: 1464: 1460: 1456: 1451: 1447: 1443: 1413: 1408: 1394: 1389: 1354: 1353: 1352: 1350: 1332: 1328: 1305: 1301: 1292: 1288: 1284: 1283:Relative risk 1280: 1263: 1260: 1257: 1237: 1234: 1231: 1209: 1205: 1201: 1196: 1192: 1169: 1165: 1161: 1156: 1152: 1143: 1142:relative risk 1139: 1120: 1116: 1113: 1108: 1105: 1100: 1094: 1090: 1086: 1081: 1077: 1073: 1067: 1059: 1055: 1050: 1044: 1040: 1032: 1028: 1023: 1017: 1013: 1006: 994: 993: 992: 990: 974: 970: 967: 964: 960: 956: 953: 948: 944: 939: 933: 929: 920: 904: 901: 898: 895: 891: 887: 884: 879: 875: 870: 864: 860: 851: 832: 828: 825: 820: 817: 812: 806: 802: 798: 793: 789: 785: 779: 771: 767: 762: 756: 752: 744: 740: 735: 729: 725: 718: 707: 703: 699: 694: 690: 682: 676: 672: 661: 657: 653: 648: 644: 636: 630: 626: 619: 616:Relative risk 607: 606: 605: 603: 602: 601:relative risk 585: 582: 579: 575: 571: 568: 563: 559: 554: 548: 544: 523: 520: 517: 513: 509: 506: 501: 497: 492: 486: 482: 473: 450: 445: 431: 426: 391: 390: 389: 387: 371: 368: 363: 359: 338: 335: 330: 326: 318:out of which 305: 302: 299: 294: 290: 269: 266: 261: 257: 236: 233: 228: 224: 216:out of which 203: 200: 197: 192: 188: 176: 170: 168: 152: 150: 146: 141: 139: 135: 131: 128:(RR) and the 127: 126:relative risk 122: 120: 116: 111: 108: 104: 100: 96: 92: 88: 84: 73: 70: 62: 52: 48: 42: 41: 35: 30: 21: 20: 13459:Epidemiology 13401: 13389: 13370: 13363: 13275:Econometrics 13225: / 13208:Chemometrics 13185:Epidemiology 13178: / 13151:Applications 12993:ARIMA model 12940:Q-statistic 12889:Stationarity 12785:Multivariate 12728: / 12724: / 12722:Multivariate 12720: / 12660: / 12656: / 12430:Bayes factor 12329:Signed rank 12241: 12215: 12207: 12195: 11890:Completeness 11726:Cohort study 11624:Opinion poll 11559:Missing data 11546:Study design 11501:Scatter plot 11423:Scatter plot 11416:Spearman's ρ 11378:Grouped data 11075: 11068: 11061: 10850:Hazard ratio 10845: 10734:Cohort study 10511: 10507: 10456: 10452: 10414: 10410: 10400: 10391: 10373: 10351: 10323: 10317: 10305: 10273:(1): 100–2. 10270: 10266: 10256: 10223: 10219: 10213: 10191:(1): 19–26. 10188: 10184: 10178: 10143: 10139: 10067: 10063: 10014: 10010: 10004: 9982:(7): 452–4. 9979: 9975: 9969: 9936: 9932: 9901:(7): 730–4. 9898: 9894: 9888: 9853: 9849: 9839: 9804: 9800: 9777:, retrieved 9773:the original 9763: 9756: 9721: 9717: 9707: 9678:Hazard ratio 9643: 9562: 9511: 9480: 9372: 9321: 9317: 9276: 9264: 9124: 8933: 8874: 8807: 8602: 8543: 8457: 8345: 8224: 8202:estimate of 8114: 7984: 7980: 7957: 7812: 7735: 7687: 7639: 7610: 7581: 7570: 7459: 7337:Case exposed 7305: 7286: 7279: 7271: 7249: 7245: 7241: 7237: 7228: 7218: 7214: 7210: 7188: 7184: 7180: 7176: 7157: 7153: 7133: 7129: 7115:0.3, or 30% 7110: 7106: 7067: 7063: 7057: 7051: 7047: 7041: 7027: 7023: 7019: 7013: 7009: 7005: 6991: 6985: 6971: 6965: 6901: 6869: 6861: 6855: 6849: 6843: 6837: 6831: 6825: 6819: 6811: 6807: 6801: 6797: 6791: 6787: 6781: 6777: 6766: 6762: 6756: 6724: 6692: 6684: 6678: 6672: 6666: 6660: 6654: 6648: 6642: 6634: 6630: 6624: 6620: 6614: 6610: 6604: 6600: 6589: 6585: 6583: 6566: 6544: 6538: 6531: 6525: 6522: 6520: 6506: 6502: 6498: 6489: 6477: 6473: 6465: 6461: 6457: 6454: 6448: 6444: 6442: 6359: 6343: 6318:epidemiology 6307: 6299: 6293: 6286: 6280: 6273: 6268: 6258: 6253: 6249: 6241: 6235: 6228: 6222: 6218: 6216: 5927: 5919: 5914: 5908: 5899: 5895: 5851: 5838: 5831: 5827: 5823: 5725: 5386: 5343: 5336: 5332: 5328: 5321: 5314: 5310: 5306: 5301: 5291: 5287: 5285: 5276: 5272: 5265: 5260: 5256: 5244: 5240: 5232: 5223: 5221: 5089: 5001: 4796: 4789: 4782: 4775: 4771: 4765: 4760: 4756: 4751: 4744: 4735: 4573: 4444: 4245: 4242: 4208: 4102: 4032: 3933: 3927: 3923: 3919: 3915: 3911: 3907: 3903: 3899: 3895: 3875: 3872: 3863: 3857: 3850: 3843: 3840: 3679: 3672: 3665: 3658: 3651: 3644: 3641: 3515: 3507: 3500: 3496: 3492: 3483: 3476: 3472: 3468: 3465: 3451: 3447: 3445: 3227: 3223: 3218: 3214: 3207: 3203: 3198: 3194: 3189: 3185: 3183: 3172:such as the 3167: 2885: 2641: 2639: 2607: 2321: 2075: 2071: 2067: 2062: 2012: 1870: 1857: 1850: 1843: 1837: 1832: 1828: 1821: 1819: 1581: 1574: 1559: 1542: 1432: 1281: 1135: 988: 921:exposed is 918: 849: 847: 599: 471: 469: 179: 166: 163: 142: 123: 112: 86: 82: 80: 65: 56: 37: 13443:Mathematics 13403:WikiProject 13318:Cartography 13280:Jurimetrics 13232:Reliability 12963:Time domain 12942:(Ljung–Box) 12864:Time-series 12742:Categorical 12726:Time-series 12718:Categorical 12653:(Bernoulli) 12488:Correlation 12468:Correlation 12264:Jarque–Bera 12236:Chi-squared 11998:M-estimator 11951:Asymptotics 11895:Sufficiency 11662:Interaction 11574:Replication 11554:Effect size 11511:Violin plot 11491:Radar chart 11471:Forest plot 11461:Correlogram 11411:Kendall's τ 11044:Null result 11003:Replication 10898:Infectivity 10820:Association 10771:Case report 10761:Case series 10744:Prospective 9673:Forest plot 9663:Cross-ratio 7313:confounding 7296:cross-ratio 6962:Events (E) 6481:effect size 3456:independent 3170:binary data 1571:dichotomous 107:independent 95:association 51:introducing 13453:Categories 13270:Demography 12988:ARMA model 12793:Regression 12370:(Friedman) 12331:(Wilcoxon) 12269:Normality 12259:Lilliefors 12206:Student's 12082:Resampling 11956:Robustness 11944:divergence 11934:Efficiency 11872:(monotone) 11867:Likelihood 11784:Population 11617:Stratified 11569:Population 11388:Dependence 11344:Count data 11275:Percentile 11252:Dispersion 11185:Arithmetic 11120:Statistics 10846:Odds ratio 10838:Risk ratio 10804:Prevalence 10790:Occurrence 10766:Case study 10504:Edwards AW 9779:2013-09-02 9694:References 9688:Rate ratio 8541:and hence 7266:See also: 7229:Odds ratio 6485:risk ratio 6421:Odds ratio 6381:Odds ratio 6219:odds ratio 5279:denotes a 5269:|/SE) 1546:invariance 1291:prevalence 1003:Odds ratio 989:odds ratio 83:odds ratio 34:references 12651:Logistic 12418:posterior 12344:Rank sum 12092:Jackknife 12087:Bootstrap 11905:Bootstrap 11840:Parameter 11789:Statistic 11584:Statistic 11496:Run chart 11481:Pie chart 11476:Histogram 11466:Fan chart 11441:Bar chart 11323:L-moments 11210:Geometric 10906:Morbidity 10894:Virulence 10796:Incidence 10084:0277-6715 9730:1719-8429 9699:Citations 9658:Cohen's h 9603:− 9582:− 9548:ψ 9528:π 9491:ψ 9455:χ 9445:McNemar's 9422:^ 9419:π 9387:^ 9384:ψ 9335:^ 9332:ψ 9232:^ 9229:π 9222:− 9203:^ 9200:π 9173:^ 9170:π 9163:− 9144:^ 9141:π 9110:ψ 9087:π 9084:− 9070:π 9064:ψ 9044:π 9012:^ 9009:π 8973:^ 8970:π 8946:π 8909:π 8883:ψ 8828:π 8816:ψ 8789:^ 8786:ψ 8756:^ 8753:ψ 8723:^ 8720:ψ 8694:^ 8691:π 8664:ψ 8644:π 8617:^ 8614:π 8557:^ 8554:ψ 8516:− 8484:^ 8481:ψ 8440:^ 8437:ψ 8392:^ 8389:ψ 8320:^ 8317:ψ 8300:^ 8297:ψ 8238:^ 8235:π 8210:π 8183:π 8092:ψ 8081:ψ 7992:π 7966:ψ 7820:ψ 7711:− 7663:− 7082:Variable 6945:Quantity 6483:when the 6417:× 6388:− 6376:≈ 6154:− 6096:− 5870:^ 5798:^ 5795:β 5785:⁡ 5750:^ 5747:β 5737:⁡ 5689:… 5661:∣ 5622:… 5594:∣ 5558:… 5530:∣ 5491:… 5463:∣ 5430:β 5423:⁡ 5406:β 5364:^ 5361:β 5062:σ 5042:⁡ 5023:∼ 4927:⁡ 4901:^ 4882:^ 4861:^ 4842:^ 4824:⁡ 4708:^ 4687:^ 4653:^ 4632:^ 4409:⁡ 4403:− 4384:⁡ 4378:− 4355:⁡ 4330:⁡ 4265:⁡ 4220:symmetric 4168:× 4155:× 4075:× 4062:× 3816:⋅ 3806:⋅ 3789:− 3755:− 3738:⋅ 3725:⋅ 3618:− 3601:− 3592:− 3575:⋅ 3562:⋅ 3414:− 3392:− 3358:− 3321:− 1670:− 1631:− 1471:≈ 1261:≈ 1235:≈ 1202:≈ 1162:≈ 1101:≈ 968:≈ 899:≈ 91:statistic 59:July 2024 13431:Medicine 13365:Category 13058:Survival 12935:Johansen 12658:Binomial 12613:Isotonic 12200:(normal) 11845:location 11652:Blocking 11607:Sampling 11486:Q–Q plot 11451:Box plot 11433:Graphics 11328:Skewness 11318:Kurtosis 11290:Variance 11220:Heronian 11215:Harmonic 11070:Glossary 11063:Category 10940:In vitro 10781:Measures 10600:Overview 10485:16012176 10248:44782438 10240:11576589 10205:15655138 10170:22429441 10100:11387977 10092:12185893 10039:11609059 9996:12377421 9961:30509187 9915:18580722 9823:11451349 9748:20842279 9652:See also 9514:Wilson's 8198:and the 8144:binomial 7213:− 7179:− 7132:− 7109:− 7090:Formula 6557:variance 5271:, where 3664:,   2636:Symmetry 2049:= 1 and 103:symmetry 13417:Portals 13391:Commons 13338:Kriging 13223:Process 13180:studies 13039:Wavelet 12872:General 12039:Plug-in 11833:L space 11612:Cluster 11313:Moments 11131:Outline 10945:In vivo 10528:2982448 10496:Sources 10476:1188107 10297:9550961 10288:1112884 10161:3289830 10031:8549701 9953:9832001 9880:3133061 9871:2545775 9831:6150799 9739:2938757 9273:Example 8773:Rothman 8632:is the 7573:Breslow 7285:Yule's 7278:Yule's 5837:, ..., 5342:, ..., 5320:, ..., 5251:p-value 4769:, with 4214:of the 3886:Example 2074: | 147:in the 143:The OR 89:) is a 47:improve 13260:Census 12850:Normal 12798:Manova 12618:Robust 12368:2-way 12360:1-way 12198:-test 11869:  11446:Biplot 11237:Median 11230:Lehmer 11172:Center 10526:  10483:  10473:  10431:727199 10429:  10330:  10295:  10285:  10246:  10238:  10203:  10168:  10158:  10098:  10090:  10082:  10037:  10029:  9994:  9959:  9951:  9913:  9878:  9868:  9829:  9821:  9746:  9736:  9728:  9606:0.9139 9596:0.9139 9585:0.6561 9575:0.6561 9512:Using 8958:. Let 8656:, and 8455:gives 7575:& 7255:0.167 7093:Value 7030:= 250 7016:= 150 6994:= 150 6988:= 135 6974:= 100 6957:Total 6553:biased 6443:where 6348:, the 5026:  5020:  5006:with: 5004:normal 4736:where 4212:logits 3686:, and 3642:where 2057:given 2013:where 1820:where 115:causal 36:, but 12884:Trend 12413:prior 12355:anova 12244:-test 12218:-test 12210:-test 12117:Power 12062:Pivot 11855:shape 11850:scale 11300:Shape 11280:Range 11225:Heinz 11200:Cubic 11136:Index 10884:Other 10524:JSTOR 10244:S2CID 10096:S2CID 10060:(PDF) 10035:S2CID 9957:S2CID 9827:S2CID 9467:13.36 8676:is a 7244:) / ( 7223:0.75 7162:0.25 7139:3.33 7128:1 / ( 7086:Abbr. 6968:= 15 6316:, in 5906:with 5904:units 1109:.0101 1106:.0526 971:.0101 902:.0526 13117:Test 12317:Sign 12169:Wald 11242:Mode 11180:Mean 10723:vs. 10591:and 10481:PMID 10427:PMID 10328:ISBN 10293:PMID 10236:PMID 10201:PMID 10166:PMID 10088:PMID 10080:ISSN 10027:PMID 9992:PMID 9949:PMID 9933:JAMA 9911:PMID 9876:PMID 9819:PMID 9744:PMID 9726:ISSN 9627:10.6 9520:for 9312:288 8997:and 8938:for 8603:Now 8222:is 7982:is 7217:) / 7183:) / 7172:RRR 7125:NNT 7103:ARR 7033:400 6997:285 6977:115 6954:(C) 6928:0.4 6925:0.2 6922:0.4 6919:0.1 6916:0.1 6913:0.1 6910:0.3 6907:0.3 6896:0.3 6893:0.1 6890:0.1 6887:0.4 6884:0.4 6881:0.4 6878:0.2 6875:0.2 6707:100 6704:100 6521:The 6278:and 6217:The 5898:and 5826:and 5385:for 5290:and 5239:exp( 5090:The 4186:0.02 4183:0.54 3902:and 3490:and 3454:are 3450:and 3212:and 3188:and 2063:i.e. 2034:and 1883:and 1562:odds 1548:and 1513:and 1250:and 1184:and 987:The 850:odds 472:risk 470:The 167:odds 99:odds 12297:BIC 12292:AIC 10516:doi 10512:126 10471:PMC 10461:doi 10457:331 10453:BMJ 10419:doi 10415:108 10283:PMC 10275:doi 10228:doi 10193:doi 10189:141 10156:PMC 10148:doi 10072:doi 10019:doi 9984:doi 9941:doi 9937:280 9903:doi 9899:101 9866:PMC 9858:doi 9854:296 9809:doi 9734:PMC 9621:1.9 9560:is 9431:0.5 9358:4.5 9301:27 9122:is 8915:0.5 8860:0.5 8742:of 8680:of 8636:of 7577:Day 7233:OR 7219:CER 7215:EER 7211:CER 7185:CER 7181:EER 7177:CER 7158:CER 7154:EER 7150:RR 7134:EER 7130:CER 7111:EER 7107:CER 7059:CER 7043:EER 6812:LOR 6802:LOR 6792:LOR 6782:LOR 6769:): 6767:LOR 6751:10 6748:20 6745:20 6742:10 6739:50 6736:50 6719:20 6716:10 6713:10 6710:20 6701:10 6698:10 6635:LOR 6625:LOR 6615:LOR 6605:LOR 6592:): 6590:LOR 5782:exp 5734:exp 5726:so 5420:exp 5331:on 5253:is 5039:log 4924:log 4821:log 4406:log 4381:log 4352:log 4327:log 4262:log 4171:0.2 4165:0.1 4158:0.6 4152:0.9 4139:0.6 4131:0.2 4126:0.1 4118:0.9 3184:If 1474:5.3 1320:or 1264:594 1258:600 1238:380 1232:400 1117:5.2 1095:594 1082:380 965:594 919:not 896:380 821:.01 818:.05 807:600 794:400 586:.01 580:600 524:.05 518:400 451:594 432:380 372:594 303:600 270:380 201:400 81:An 13455:: 10920:, 10916:, 10912:, 10908:, 10904:, 10900:, 10896:, 10892:, 10874:, 10870:, 10866:, 10848:, 10844:, 10840:, 10836:, 10832:, 10828:, 10810:, 10806:, 10802:, 10798:, 10727:, 10522:. 10479:. 10469:. 10455:. 10451:. 10439:^ 10425:. 10413:. 10409:. 10382:^ 10360:^ 10342:^ 10291:. 10281:. 10271:31 10269:. 10265:. 10242:. 10234:. 10224:98 10222:. 10199:. 10187:. 10164:. 10154:. 10144:62 10142:. 10138:. 10126:^ 10108:^ 10094:. 10086:. 10078:. 10068:21 10066:. 10062:. 10047:^ 10033:. 10025:. 10015:11 10013:. 9990:. 9980:12 9978:. 9955:. 9947:. 9935:. 9923:^ 9909:. 9897:. 9874:. 9864:. 9852:. 9848:. 9825:. 9817:. 9805:22 9803:. 9799:. 9787:^ 9767:, 9742:. 9732:. 9722:19 9720:. 9716:. 9370:. 9344:27 9262:. 8931:. 8872:. 8600:. 8586:01 8571:10 8524:10 8511:01 8498:10 8470:10 8429:10 8375:01 8362:10 8283:01 8270:10 8252:10 8175:01 8162:10 8128:10 7554:00 7527:01 7500:10 7473:11 7441:00 7413:01 7380:10 7352:11 7306:A 7298:. 7283:, 7252:) 7250:CN 7248:/ 7246:CE 7242:EN 7240:/ 7238:EE 7203:PF 7189:RR 7156:/ 7136:) 7073:— 7068:CS 7066:/ 7064:CE 7062:= 7052:ES 7050:/ 7048:EE 7046:= 7028:CN 7026:+ 7024:CE 7022:= 7020:CS 7014:EN 7012:+ 7010:EE 7008:= 7006:ES 6992:CN 6986:EN 6972:CE 6966:EE 6808:OR 6798:OR 6788:OR 6778:OR 6763:OR 6733:5 6730:5 6631:OR 6621:OR 6611:OR 6601:OR 6586:OR 6576:. 6559:. 6548:01 6542:10 6535:00 6529:11 6256:. 6245:10 6239:01 6232:00 6226:11 6193:00 6180:01 6168:00 6135:00 6122:01 6110:01 6064:10 6051:11 6039:10 6018:10 6005:11 5993:11 5335:, 5283:. 5198:00 5176:01 5154:10 5132:11 4975:01 4965:10 4953:00 4943:11 4908:01 4889:10 4868:00 4849:11 4800:00 4793:01 4786:10 4779:11 4761:ij 4752:ij 4715:00 4694:01 4660:10 4639:11 4553:00 4541:01 4516:10 4504:11 4420:01 4395:10 4366:00 4341:11 4312:10 4302:01 4290:00 4280:11 4194:27 4088:27 4078:20 4072:10 4065:60 4059:90 4014:60 4009:10 3991:20 3986:90 3879:11 3870:. 3867:•1 3861:1• 3854:11 3683:01 3676:11 3669:•1 3662:10 3655:11 3648:1• 3534:11 3511:01 3504:11 3487:10 3480:11 3458:. 3144:01 3134:10 3122:00 3112:11 3088:00 3075:10 3057:00 3042:00 3029:10 3011:10 2983:01 2970:11 2952:01 2937:01 2924:11 2906:11 2862:00 2849:10 2838:00 2821:01 2808:11 2797:01 2767:00 2754:10 2743:10 2726:01 2713:11 2702:11 2644:, 2588:01 2578:10 2566:00 2556:11 2533:00 2520:01 2502:00 2487:00 2474:01 2456:01 2428:10 2415:11 2397:10 2382:10 2369:11 2351:11 2298:00 2285:01 2274:00 2257:00 2244:01 2233:01 2203:10 2190:11 2179:10 2162:10 2149:11 2138:11 2080:: 2065:, 2061:, 2039:00 2032:01 2027:, 2025:10 2020:, 2018:11 1992:00 1980:01 1955:10 1943:11 1552:. 1465:16 1452:10 1444:20 1414:16 1395:10 1390:20 1279:. 1074:20 888:20 786:20 604:. 510:20 427:20 388:: 237:20 151:. 87:OR 13419:: 12242:G 12216:F 12208:t 12196:Z 11915:V 11910:U 11112:e 11105:t 11098:v 10757:) 10753:( 10714:) 10710:( 10661:) 10657:( 10581:e 10574:t 10567:v 10530:. 10518:: 10487:. 10463:: 10433:. 10421:: 10336:. 10299:. 10277:: 10250:. 10230:: 10207:. 10195:: 10172:. 10150:: 10120:. 10102:. 10074:: 10041:. 10021:: 9998:. 9986:: 9963:. 9943:: 9917:. 9905:: 9882:. 9860:: 9833:. 9811:: 9750:. 9630:) 9624:, 9618:( 9615:= 9612:) 9600:1 9591:, 9579:1 9570:( 9497:1 9494:= 9481:P 9464:= 9459:2 9428:= 9396:1 9393:= 9355:= 9352:6 9348:/ 9341:= 9309:6 9298:5 9250:) 9242:B 9239:U 9219:1 9213:B 9210:U 9191:, 9183:B 9180:L 9160:1 9154:B 9151:L 9132:( 9090:) 9081:1 9078:( 9074:/ 9067:= 9022:B 9019:U 8983:B 8980:L 8912:= 8889:1 8886:= 8857:= 8854:) 8851:1 8848:+ 8845:1 8842:( 8838:/ 8834:1 8831:= 8825:, 8822:1 8819:= 8582:n 8577:/ 8567:n 8563:= 8529:) 8520:n 8507:n 8503:+ 8494:n 8490:( 8475:= 8466:n 8425:n 8404:) 8401:1 8398:+ 8383:( 8380:) 8371:n 8367:+ 8358:n 8354:( 8332:) 8329:1 8326:+ 8311:( 8307:/ 8291:= 8288:) 8279:n 8275:+ 8266:n 8262:( 8258:/ 8248:n 8244:= 8186:) 8180:, 8171:n 8167:+ 8158:n 8154:( 8124:n 8101:) 8098:1 8095:+ 8089:( 8085:/ 8078:= 8075:) 8070:0 8066:p 8060:1 8056:q 8052:+ 8047:0 8043:q 8037:1 8033:p 8029:( 8025:/ 8021:) 8016:0 8012:q 8006:1 8002:p 7998:( 7995:= 7944:) 7939:0 7935:p 7929:1 7925:q 7921:( 7917:/ 7911:0 7907:q 7901:1 7897:p 7893:= 7890:) 7885:0 7881:q 7876:/ 7870:0 7866:p 7862:( 7858:/ 7854:) 7849:1 7845:q 7840:/ 7834:1 7830:p 7826:( 7823:= 7796:1 7792:q 7786:0 7782:p 7759:0 7755:q 7749:1 7745:p 7719:0 7715:p 7708:1 7705:= 7700:0 7696:q 7671:1 7667:p 7660:1 7657:= 7652:1 7648:q 7623:0 7619:p 7594:1 7590:p 7550:n 7523:n 7496:n 7469:n 7437:n 7409:n 7376:n 7348:n 7287:Q 7280:Y 7236:( 7209:( 7205:u 7175:( 6902:X 6870:X 6862:Y 6856:Y 6850:Y 6844:Y 6838:Y 6832:Y 6826:Y 6820:Y 6725:X 6693:X 6685:Y 6679:Y 6673:Y 6667:Y 6661:Y 6655:Y 6649:Y 6643:Y 6545:n 6539:n 6532:n 6526:n 6449:C 6445:R 6425:) 6412:C 6408:R 6404:( 6401:+ 6396:C 6392:R 6385:1 6294:X 6287:Y 6281:X 6274:X 6269:X 6254:f 6250:f 6242:p 6236:p 6229:p 6223:p 6189:p 6185:+ 6176:p 6164:p 6160:) 6157:f 6151:1 6148:( 6131:p 6127:+ 6118:p 6106:p 6102:) 6099:f 6093:1 6090:( 6082:0 6079:= 6076:X 6060:p 6056:+ 6047:p 6035:p 6031:f 6014:p 6010:+ 6001:p 5989:p 5985:f 5977:1 5974:= 5971:X 5964:0 5961:= 5958:Y 5953:1 5950:= 5947:Y 5928:f 5920:X 5915:f 5909:X 5900:Y 5896:X 5880:j 5877:i 5865:p 5841:p 5839:Z 5835:1 5832:Z 5828:X 5824:Y 5810:) 5805:x 5788:( 5762:) 5757:x 5740:( 5711:, 5705:) 5700:p 5696:Z 5692:, 5686:, 5681:1 5677:Z 5673:, 5670:0 5667:= 5664:X 5658:0 5655:= 5652:Y 5649:( 5646:P 5642:/ 5638:) 5633:p 5629:Z 5625:, 5619:, 5614:1 5610:Z 5606:, 5603:0 5600:= 5597:X 5591:1 5588:= 5585:Y 5582:( 5579:P 5574:) 5569:p 5565:Z 5561:, 5555:, 5550:1 5546:Z 5542:, 5539:1 5536:= 5533:X 5527:0 5524:= 5521:Y 5518:( 5515:P 5511:/ 5507:) 5502:p 5498:Z 5494:, 5488:, 5483:1 5479:Z 5475:, 5472:1 5469:= 5466:X 5460:1 5457:= 5454:Y 5451:( 5448:P 5442:= 5439:) 5434:x 5426:( 5417:= 5410:x 5401:e 5387:X 5371:x 5346:p 5344:Z 5339:1 5337:Z 5333:X 5329:Y 5324:p 5322:Z 5318:1 5315:Z 5311:X 5307:Y 5292:Y 5288:X 5277:Z 5273:P 5266:L 5261:Z 5259:( 5257:P 5255:2 5245:L 5241:L 5233:L 5224:L 5218:. 5194:n 5190:1 5184:+ 5172:n 5168:1 5162:+ 5150:n 5146:1 5140:+ 5128:n 5124:1 5116:= 5111:E 5108:S 5074:. 5071:) 5066:2 5057:, 5054:) 5051:R 5048:O 5045:( 5036:( 5031:N 5017:L 4998:. 4984:) 4971:n 4961:n 4949:n 4939:n 4931:( 4921:= 4917:) 4898:p 4879:p 4858:p 4839:p 4828:( 4818:= 4815:L 4797:n 4790:n 4783:n 4776:n 4772:n 4766:n 4757:n 4745:p 4741:︿ 4705:p 4684:p 4675:0 4672:= 4669:X 4650:p 4629:p 4620:1 4617:= 4614:X 4607:0 4604:= 4601:Y 4596:1 4593:= 4590:Y 4549:n 4537:n 4531:0 4528:= 4525:X 4512:n 4500:n 4494:1 4491:= 4488:X 4481:0 4478:= 4475:Y 4470:1 4467:= 4464:Y 4429:. 4425:) 4416:p 4412:( 4400:) 4391:p 4387:( 4373:) 4362:p 4358:( 4349:+ 4346:) 4337:p 4333:( 4324:= 4320:) 4308:p 4298:p 4286:p 4276:p 4269:( 4191:= 4178:= 4145:= 4135:/ 4122:/ 4085:= 4052:= 4048:R 4045:O 4004:0 4001:= 3998:D 3981:1 3978:= 3975:D 3968:0 3965:= 3962:M 3957:1 3954:= 3951:M 3928:A 3924:X 3920:B 3916:X 3912:A 3908:B 3904:B 3900:A 3896:X 3876:p 3864:p 3858:p 3851:p 3844:R 3826:. 3819:1 3812:p 3803:1 3799:p 3795:) 3792:R 3786:1 3783:( 3780:R 3777:4 3774:+ 3769:2 3765:) 3761:) 3758:1 3752:R 3749:( 3746:) 3741:1 3734:p 3730:+ 3722:1 3718:p 3714:( 3711:+ 3708:1 3705:( 3700:= 3697:S 3680:p 3673:p 3666:p 3659:p 3652:p 3645:p 3624:) 3621:1 3615:R 3612:( 3609:2 3604:S 3598:) 3595:1 3589:R 3586:( 3583:) 3578:1 3571:p 3567:+ 3559:1 3555:p 3551:( 3548:+ 3545:1 3539:= 3530:p 3516:R 3508:p 3501:p 3497:Y 3495:( 3493:P 3484:p 3477:p 3473:X 3471:( 3469:P 3452:Y 3448:X 3427:) 3422:y 3418:p 3411:1 3408:( 3405:) 3400:x 3396:p 3389:1 3386:( 3379:y 3375:p 3371:) 3366:x 3362:p 3355:1 3352:( 3347:0 3344:= 3341:X 3334:) 3329:y 3325:p 3318:1 3315:( 3310:x 3306:p 3298:y 3294:p 3288:x 3284:p 3278:1 3275:= 3272:X 3265:0 3262:= 3259:Y 3254:1 3251:= 3248:Y 3228:Y 3226:( 3224:P 3219:y 3215:p 3208:X 3206:( 3204:P 3199:x 3195:p 3190:Y 3186:X 3153:. 3140:p 3130:p 3118:p 3108:p 3100:= 3093:) 3084:p 3080:+ 3071:p 3067:( 3063:/ 3053:p 3047:) 3038:p 3034:+ 3025:p 3021:( 3017:/ 3007:p 2997:/ 2988:) 2979:p 2975:+ 2966:p 2962:( 2958:/ 2948:p 2942:) 2933:p 2929:+ 2920:p 2916:( 2912:/ 2902:p 2858:p 2854:+ 2845:p 2834:p 2817:p 2813:+ 2804:p 2793:p 2785:0 2782:= 2779:X 2763:p 2759:+ 2750:p 2739:p 2722:p 2718:+ 2709:p 2698:p 2690:1 2687:= 2684:X 2677:0 2674:= 2671:Y 2666:1 2663:= 2660:Y 2642:Y 2630:) 2628:Y 2624:X 2622:( 2618:) 2616:Y 2612:X 2610:( 2584:p 2574:p 2562:p 2552:p 2545:= 2538:) 2529:p 2525:+ 2516:p 2512:( 2508:/ 2498:p 2492:) 2483:p 2479:+ 2470:p 2466:( 2462:/ 2452:p 2442:/ 2433:) 2424:p 2420:+ 2411:p 2407:( 2403:/ 2393:p 2387:) 2378:p 2374:+ 2365:p 2361:( 2357:/ 2347:p 2339:= 2336:R 2333:O 2294:p 2290:+ 2281:p 2270:p 2253:p 2249:+ 2240:p 2229:p 2221:0 2218:= 2215:X 2199:p 2195:+ 2186:p 2175:p 2158:p 2154:+ 2145:p 2134:p 2126:1 2123:= 2120:X 2113:0 2110:= 2107:Y 2102:1 2099:= 2096:Y 2078:) 2076:X 2072:Y 2070:( 2068:P 2059:X 2051:X 2047:X 2043:Y 2036:p 2029:p 2022:p 2015:p 1988:p 1976:p 1970:0 1967:= 1964:X 1951:p 1939:p 1933:1 1930:= 1927:X 1920:0 1917:= 1914:Y 1909:1 1906:= 1903:Y 1885:Y 1881:X 1861:1 1858:q 1854:2 1851:p 1847:1 1844:q 1841:2 1838:p 1833:x 1829:p 1825:x 1822:q 1805:, 1796:1 1792:q 1786:2 1782:p 1772:2 1768:q 1762:1 1758:p 1750:= 1742:2 1738:q 1733:/ 1727:2 1723:p 1715:1 1711:q 1706:/ 1700:1 1696:p 1689:= 1683:) 1678:2 1674:p 1667:1 1664:( 1660:/ 1654:2 1650:p 1644:) 1639:1 1635:p 1628:1 1625:( 1621:/ 1615:1 1611:p 1604:= 1601:R 1598:O 1585:2 1582:p 1578:1 1575:p 1526:N 1522:V 1499:E 1495:V 1461:/ 1457:6 1448:/ 1409:6 1333:N 1329:V 1306:E 1302:V 1267:) 1210:N 1206:H 1197:N 1193:V 1170:E 1166:H 1157:E 1153:V 1121:. 1114:= 1091:/ 1087:6 1078:/ 1068:= 1060:N 1056:H 1051:/ 1045:N 1041:D 1033:E 1029:H 1024:/ 1018:E 1014:D 1007:= 975:. 961:/ 957:6 954:= 949:N 945:H 940:/ 934:N 930:D 905:, 892:/ 885:= 880:E 876:H 871:/ 865:E 861:D 833:. 829:5 826:= 813:= 803:/ 799:6 790:/ 780:= 772:N 768:V 763:/ 757:N 753:D 745:E 741:V 736:/ 730:E 726:D 719:= 713:) 708:N 704:H 700:+ 695:N 691:D 687:( 683:/ 677:N 673:D 667:) 662:E 658:H 654:+ 649:E 645:D 641:( 637:/ 631:E 627:D 620:= 583:= 576:/ 572:6 569:= 564:N 560:V 555:/ 549:N 545:D 521:= 514:/ 507:= 502:E 498:V 493:/ 487:E 483:D 446:6 369:= 364:N 360:H 339:6 336:= 331:N 327:D 306:, 300:= 295:N 291:V 267:= 262:E 258:H 234:= 229:E 225:D 204:, 198:= 193:E 189:V 85:( 72:) 66:( 61:) 57:( 43:.

Index

references
inline citations
improve
introducing
Learn how and when to remove this message
statistic
association
odds
symmetry
independent
causal
does not imply causation
relative risk
absolute risk reduction
case-control studies
rare disease assumption
plays an important role
logistic model
rare disease assumption
contingency table
relative risk
rare-disease case
relative risk
Relative risk
random sampling
prevalence
case-control study
invariance
insensitivity to the type of sampling
odds

Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.

↑