294:, is another form of Attrition bias, mainly occurring in medicinal studies over a lengthy time period. Non-Response or Retention bias can be influenced by a number of both tangible and intangible factors, such as; wealth, education, altruism, initial understanding of the study and its requirements. Researchers may also be incapable of conducting follow-up contact resulting from inadequate identifying information and contact details collected during the initial recruitment and research phase.
332:
lower socio-economic background. Furthermore, another study shows that women are more probable to volunteer for studies than males. Volunteer bias is evident throughout the study life-cycle, from recruitment to follow-ups. More generally speaking volunteer response can be put down to individual altruism, a desire for approval, personal relation to the study topic and other reasons. As with most instances mitigation in the case of volunteer bias is an increased sample size.
284:. It gives biased results where it is unequal in regard to exposure and/or outcome. For example, in a test of a dieting program, the researcher may simply reject everyone who drops out of the trial, but most of those who drop out are those for whom it was not working. Different loss of subjects in intervention and comparison group may change the characteristics of these groups and outcomes irrespective of the studied
175:, a potential mixup between cause and effect when exposure is dependent on indication, e.g. a treatment is given to people in high risk of acquiring a disease, potentially causing a preponderance of treated people among those acquiring the disease. This may cause an erroneous appearance of the treatment being a cause of the disease.
331:
Self-selection bias or a volunteer bias in studies offer further threats to the validity of a study as these participants may have intrinsically different characteristics from the target population of the study. Studies have shown that volunteers tend to come from a higher social standing than from a
318:
record of Earth: if large impacts cause mass extinctions and ecological disruptions precluding the evolution of intelligent observers for long periods, no one will observe any evidence of large impacts in the recent past (since they would have prevented intelligent observers from evolving). Hence
306:
has argued that data are filtered not only by study design and measurement, but by the necessary precondition that there has to be someone doing a study. In situations where the existence of the observer or the study is correlated with the data, observation selection effects occur, and
392:, the general tendency of humans to give more attention to whatever confirms our pre-existing perspective; or specifically in experimental science, the distortion produced by experiments that are designed to seek confirmatory evidence instead of trying to disprove the hypothesis.
37:
introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. It is sometimes referred to as the
165:, when a treatment for the first symptoms of a disease or other outcome appear to cause the outcome. It is a potential bias when there is a lag time from the first symptoms and start of treatment before actual diagnosis. It can be mitigated by
203:, when specific subsets of data are chosen to support a conclusion (e.g. citing examples of plane crashes as evidence of airline flight being unsafe, while ignoring the far more common example of flights that complete safely. See:
93:
for differences or similarities found in the sample at hand. In this sense, errors occurring in the process of gathering the sample or cohort cause sampling bias, while errors in any process thereafter cause selection bias.
237:
Performing repeated experiments and reporting only the most favorable results, perhaps relabelling lab records of other experiments as "calibration tests", "instrumentation errors" or "preliminary surveys".
907:
Jordan, Sue; Watkins, Alan; Storey, Mel; Allen, Steven J.; Brooks, Caroline J.; Garaiova, Iveta; Heaven, Martin L.; Jones, Ruth; Plummer, Sue F.; Russell, Ian T.; Thornton, Catherine A. (2013-07-09).
101:, pre-screening of trial participants, discounting trial subjects/tests that did not run to completion and migration bias by excluding subjects who have recently moved into or out of the study area,
909:"Volunteer Bias in Recruitment, Retention, and Blood Sample Donation in a Randomised Controlled Trial Involving Mothers and Their Children at Six Months and Two Years: A Longitudinal Analysis"
363:
When data are selected for fitting or forecast purposes, a coalitional game can be set up so that a fitting or forecast accuracy function can be defined on all subsets of the data variables.
78:(or non-human factors) in which all participants are not equally balanced or objectively represented. It is mostly classified as a subtype of selection bias, sometimes specifically termed
395:
exclusion bias, results from applying different criteria to cases and controls in regards to participation eligibility for a study/different variables serving as basis for exclusion.
360:
determinants of selection into the sample which bias estimates, and this correlation between unobservables cannot be directly assessed by the observed determinants of treatment.
386:
by not publishing uninteresting (usually negative) results, or results which go against the experimenter's prejudices, a sponsor's interests, or community expectations.
256:
is a kind of selection bias caused by attrition (loss of participants), discounting trial subjects/tests that did not run to completion. It is closely related to the
151:, when one disease predisposes for a second disease, and the treatment for the first disease erroneously appears to predispose to the second disease. For example,
187:
Partitioning (dividing) data with knowledge of the contents of the partitions, and then analyzing them with tests designed for blindly chosen partitions.
1999:
46:, resulting from the method of collecting samples. If the selection bias is not taken into account, then some conclusions of the study may be false.
1889:
1864:
210:
Rejection of bad data on (1) arbitrary grounds, instead of according to previously stated or generally agreed criteria or (2) discarding "
109:, where disease is diagnosed earlier for participants than in comparison populations, although the average course of disease is the same.
761:
Tamim H; Monfared AA; LeLorier J (March 2007). "Application of lag-time into exposure definitions to control for protopathic bias".
2291:
2287:
734:
Feinstein AR; Horwitz RI (November 1978). "A critique of the statistical evidence associating estrogens with endometrial cancer".
2337:
2295:
2283:
1894:
1054:Ćirković, M. M.; Sandberg, A.; Bostrom, N. (2010). "Anthropic Shadow: Observation Selection Effects and Human Extinction Risks".
1992:
89:
of a test (the ability of its results to be generalized to the rest of the population), while selection bias mainly addresses
1038:
813:
715:
636:
214:" on statistical grounds that fail to take into account important information that could be derived from "wild" observations.
2458:
2374:
159:, so estrogens given for the postmenopausal syndrome may receive a higher than actual blame for causing endometrial cancer.
344:
may be used in special cases. An assessment of the degree of selection bias can be made by examining correlations between
2239:
594:
Cortes, Corinna; Mohri, Mehryar; Riley, Michael; Rostamizadeh, Afshin (2008). "Sample
Selection Bias Correction Theory".
244:
as if it were a single experiment (which is logically the same as the previous item, but is seen as much less dishonest).
2209:
1985:
66:
of a population, causing some members of the population to be less likely to be included than others, resulting in a
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17:
340:
In the general case, selection biases cannot be overcome with statistical analysis of existing data alone, though
1966:
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might similarly be underestimated due to selection bias, and an anthropic correction has to be introduced.
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A distinction of sampling bias (albeit not a universally accepted one) is that it undermines the
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2012:
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1977:
409: – Tendency to misinterpret statistical experiments involving conditional probabilities
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1679:
1531:
1407:
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1063:
920:
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466:
406:
43:
169:, that is, exclusion of exposures that occurred in a certain time period before diagnosis.
8:
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reasons), but the extreme value is likely to be reached by the variable with the largest
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260:, where only the subjects that "survived" a process are included in the analysis or the
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1476:
1466:
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642:
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531:. Retrieved on 2009-09-23. Site in turn cites: Mosby's Medical Dictionary, 8th edition.
442:
424:
341:
156:
118:
Early termination of a trial at a time when its results support the desired conclusion.
71:
991:
571:
554:
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2008:
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1003:
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938:
886:
809:
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711:
632:
576:
555:"The effects of sample selection bias on racial differences in child abuse reporting"
484:
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389:
320:
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86:
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448:
375:
102:
662:"Domain adaptation and sample bias correction theory and algorithm for regression"
646:
193:
alteration of data inclusion based on arbitrary or subjective reasons, including:
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2245:
2200:
1879:
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1646:
1626:
1541:
1444:
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1365:
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933:
705:
540:
1162:
Tripepi, Giovanni; Jager, Kitty J.; Dekker, Friedo W.; Zoccali, Carmine (2010).
628:
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1536:
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1360:
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661:
454:
418:
379:
152:
106:
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690:
451: – Higher probability of publishing results showing a significant finding
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2427:
2394:
2389:
1859:
1839:
1802:
1776:
1761:
1741:
1721:
1684:
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1556:
1551:
1546:
1424:
1328:
1189:
999:
942:
460:
439: – Systematic patterns of deviation from norm or rationality in judgment
433: – Tendency of a scientific study to support the interests of its funder
383:
241:
227:
67:
63:
59:
264:, where only the subjects that "failed" a process are included. It includes
2269:
2153:
1819:
1581:
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1506:
1496:
1486:
1382:
1239:
Heckman, J. J. (1979). "Sample
Selection Bias as a Specification Error".
881:
864:
747:
105:, where slowly developing disease with better prognosis is detected, and
830:
2265:
2257:
2223:
2185:
2092:
1854:
1849:
1824:
1260:
1031:
Anthropic Bias: Observation
Selection Effects in Science and Philosophy
42:. The phrase "selection bias" most often refers to the distortion of a
1180:
319:
there is a potential bias in the impact record of Earth. Astronomical
2325:
2313:
1942:
1429:
774:
603:. Lecture Notes in Computer Science. Vol. 5254. pp. 38–53.
345:
1252:
1131:
1106:
2359:
1901:
1786:
126:
609:
2364:
808:. Philadelphia, Pa: American College of Physicians. p. 159.
211:
122:
121:
A trial may be terminated early at an extreme value (often for
348:(background) variables and a treatment indicator. However, in
2007:
760:
593:
1300:
469: – Theory relating to sampling from finite populations
130:
34:
1164:"Selection Bias and Information Bias in Clinical Research"
27:
Bias in a statistical analysis due to non-random selection
1269:
1161:
865:"Empirical evidence of attrition bias in clinical trials"
906:
1053:
553:
Ards, Sheila; Chung, Chanjin; Myers, Samuel L. (1998).
733:
155:
syndrome gives a higher likelihood of also developing
806:
Hypertension (Key
Diseases) (Acp Key Diseases Series)
382:, the distortion produced in community perception or
481: – Prediction that causes itself to become true
82:, but some classify it as a separate type of bias.
710:. Lippincott Williams & Wilkins. p. 262.
1107:"Astrophysics: Is a doomsday catastrophe likely?"
2510:
982:. Originally published as Volume 1, Issue 7497.
475: – Theory within the practice of psychology
803:
1104:
653:
587:
552:
1993:
1285:
487: – Logical error, form of selection bias
415: – Theory of response to surprise events
546:
463: – Bias in the sampling of a population
457: – Bias in the reporting of information
240:Presenting the most significant result of a
199:, which actually is not selection bias, but
822:
659:
541:Dictionary of Cancer Terms → Selection Bias
505:Dictionary of Cancer Terms → selection bias
226:Selection of which studies to include in a
2000:
1986:
1948:Heuristics in judgment and decision-making
1292:
1278:
729:
727:
1179:
1130:
950:
932:
902:
900:
880:
862:
680:
618:
608:
570:
2292:Preventable fraction among the unexposed
2288:Attributable fraction for the population
697:
660:Cortes, Corinna; Mohri, Mehryar (2014).
2296:Preventable fraction for the population
2284:Attributable fraction among the exposed
1238:
1028:
858:
856:
828:
724:
129:, even if all variables have a similar
14:
2511:
897:
421: – Fallacy of incomplete evidence
371:Selection bias is closely related to:
1981:
1273:
1209:
1207:
973:
869:International Journal of Epidemiology
703:
297:
2459:Correlation does not imply causation
2375:Animal testing on non-human primates
853:
517:Medical Dictionary - 'Sampling Bias'
831:"Some Remarks on Wild Observations"
24:
1204:
863:JĂĽni, P.; Egger, Matthias (2005).
543:. Retrieved on September 23, 2009.
507:. Retrieved on September 23, 2009.
352:models, it is correlation between
97:Examples of sampling bias include
25:
2545:
1105:Tegmark, M.; Bostrom, N. (2005).
529:TheFreeDictionary → biased sample
366:
326:
62:is systematic error due to a non-
1076:10.1111/j.1539-6924.2010.01460.x
356:determinants of the outcome and
112:
54:
49:
1232:
1155:
1098:
1047:
1022:
967:
797:
754:
519:Retrieved on September 23, 2009
2342:Pre- and post-test probability
2064:Patient and public involvement
847:10.1080/00401706.1960.10489875
534:
522:
510:
498:
13:
1:
992:10.1016/S0140-6736(67)92377-X
572:10.1016/S0145-2134(97)00131-2
492:
335:
2469:Sex as a biological variable
934:10.1371/journal.pone.0067912
829:Kruskal, William H. (1960).
669:Theoretical Computer Science
248:
149:Clinical susceptibility bias
7:
2433:Intention-to-treat analysis
2405:Analysis of clinical trials
2334:Specificity and sensitivity
2088:Randomized controlled trial
1814:DĂ©formation professionnelle
974:Small, W. P. (1967-05-06).
629:10.1007/978-3-540-87987-9_8
597:Algorithmic Learning Theory
399:
232:combinatorial meta-analysis
137:
10:
2550:
1808:Basking in reflected glory
1299:
763:Pharmacoepidemiol Drug Saf
220:
2477:
2442:Interpretation of results
2441:
2403:
2352:
2302:
2276:
2238:
2208:
2199:
2175:Nested case–control study
2125:
2072:
2019:
1956:
1938:Cognitive bias mitigation
1930:
1795:
1670:
1307:
1168:Nephron Clinical Practice
691:10.1016/j.tcs.2013.09.027
559:Child Abuse & Neglect
473:Selective exposure theory
2044:Academic clinical trials
1522:Illusion of transparency
804:Matthew R. Weir (2005).
479:Self-fulfilling prophecy
437:List of cognitive biases
2262:Relative risk reduction
2110:Adaptive clinical trial
2054:Evidence-based medicine
2037:Adaptive clinical trial
1033:. New York: Routledge.
704:Fadem, Barbara (2009).
314:An example is the past
181:
2250:Number needed to treat
1029:Bostrom, Nick (2002).
427: – Cognitive bias
205:availability heuristic
2519:Sampling (statistics)
2254:Number needed to harm
2141:Cross-sectional study
2093:Scientific experiment
2049:Clinical study design
1890:Arab–Israeli conflict
1617:Social influence bias
1562:Out-group homogeneity
80:sample selection bias
2220:Cumulative incidence
1532:Mere-exposure effect
1462:Extrinsic incentives
1408:Selective perception
467:Sampling probability
445: – Type of bias
44:statistical analysis
2127:Observational study
2059:Real world evidence
2013:experimental design
1757:Social desirability
1652:von Restorff effect
1527:Mean world syndrome
1502:Hostile attribution
1123:2005Natur.438..754T
1068:2010RiskA..30.1495C
976:"Lost to Follow-Up"
925:2013PLoSO...867912J
742:(11 Pt 2): 4001–5.
309:anthropic reasoning
144:Susceptibility bias
2413:Risk–benefit ratio
2380:First-in-man study
2330:Case fatality rate
2171:Case–control study
2145:Longitudinal study
1672:Statistical biases
1450:Curse of knowledge
882:10.1093/ije/dyh406
707:Behavioral Science
443:Participation bias
425:Frequency illusion
342:Heckman correction
298:Observer selection
282:protocol deviators
157:endometrial cancer
72:statistical sample
2529:Scientific method
2524:Experimental bias
2506:
2505:
2454:Survivorship bias
2418:Systematic review
2385:Multicenter trial
2348:
2347:
2338:Likelihood-ratios
2310:Clinical endpoint
2278:Population impact
2232:Period prevalence
2009:Clinical research
1975:
1974:
1612:Social comparison
1393:Choice-supportive
1181:10.1159/000312871
1040:978-0-415-93858-7
986:(7497): 997–999.
815:978-1-930513-58-7
717:978-0-7817-8257-9
638:978-3-540-87986-2
485:Survivorship bias
413:Black swan theory
407:Berkson's paradox
390:confirmation bias
321:existential risks
292:Lost to follow-up
258:survivorship bias
201:confirmation bias
91:internal validity
87:external validity
16:(Redirected from
2541:
2534:Causal inference
2353:Trial/test types
2228:Point prevalence
2206:
2205:
2149:Ecological study
2132:EBM II-2 to II-3
2103:Open-label trial
2098:Blind experiment
2074:Controlled study
2002:
1995:
1988:
1979:
1978:
1772:Systematic error
1727:Omitted-variable
1642:Trait ascription
1482:Frog pond effect
1310:Cognitive biases
1294:
1287:
1280:
1271:
1270:
1265:
1264:
1236:
1230:
1229:
1227:
1226:
1215:"Volunteer bias"
1211:
1202:
1201:
1183:
1159:
1153:
1152:
1134:
1102:
1096:
1095:
1062:(10): 1495–506.
1051:
1045:
1044:
1026:
1020:
1019:
971:
965:
964:
954:
936:
904:
895:
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775:10.1002/pds.1360
758:
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731:
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602:
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584:
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550:
544:
538:
532:
526:
520:
514:
508:
502:
449:Publication bias
376:publication bias
163:Protopathic bias
103:length-time bias
40:selection effect
21:
18:Law of selection
2549:
2548:
2544:
2543:
2542:
2540:
2539:
2538:
2509:
2508:
2507:
2502:
2473:
2437:
2399:
2344:
2298:
2272:
2246:Risk difference
2234:
2195:
2129:
2121:
2076:
2068:
2032:Trial protocols
2015:
2006:
1976:
1971:
1952:
1926:
1791:
1666:
1647:Turkey illusion
1415:Compassion fade
1312:
1303:
1298:
1268:
1253:10.2307/1912352
1237:
1233:
1224:
1222:
1219:Catalog of Bias
1213:
1212:
1205:
1160:
1156:
1132:10.1038/438754a
1103:
1099:
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1048:
1041:
1027:
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827:
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718:
702:
698:
682:10.1.1.367.6899
664:
658:
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639:
620:10.1.1.144.4478
600:
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515:
511:
503:
499:
495:
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402:
369:
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251:
223:
184:
173:Indication bias
140:
115:
70:, defined as a
57:
52:
28:
23:
22:
15:
12:
11:
5:
2547:
2537:
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2504:
2503:
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2500:
2497:List of topics
2493:
2486:
2478:
2475:
2474:
2472:
2471:
2466:
2461:
2456:
2451:
2449:Selection bias
2445:
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2420:
2415:
2409:
2407:
2401:
2400:
2398:
2397:
2392:
2387:
2382:
2377:
2372:
2370:Animal testing
2367:
2362:
2356:
2354:
2350:
2349:
2346:
2345:
2322:Mortality rate
2308:
2306:
2300:
2299:
2282:
2280:
2274:
2273:
2244:
2242:
2236:
2235:
2214:
2212:
2203:
2197:
2196:
2194:
2193:
2188:
2183:
2178:
2168:
2167:
2166:
2161:
2151:
2137:
2135:
2123:
2122:
2120:
2119:
2118:
2117:
2115:Platform trial
2107:
2106:
2105:
2100:
2095:
2084:
2082:
2070:
2069:
2067:
2066:
2061:
2056:
2051:
2046:
2041:
2040:
2039:
2034:
2027:Clinical trial
2023:
2021:
2017:
2016:
2005:
2004:
1997:
1990:
1982:
1973:
1972:
1970:
1969:
1964:
1957:
1954:
1953:
1951:
1950:
1945:
1940:
1934:
1932:
1931:Bias reduction
1928:
1927:
1925:
1924:
1919:
1914:
1909:
1907:Political bias
1904:
1899:
1898:
1897:
1892:
1887:
1882:
1877:
1872:
1867:
1862:
1852:
1847:
1842:
1837:
1835:Infrastructure
1832:
1827:
1822:
1817:
1810:
1805:
1799:
1797:
1793:
1792:
1790:
1789:
1784:
1779:
1774:
1769:
1764:
1759:
1754:
1752:Self-selection
1749:
1744:
1739:
1734:
1729:
1724:
1719:
1714:
1709:
1704:
1703:
1702:
1692:
1687:
1682:
1676:
1674:
1668:
1667:
1665:
1664:
1659:
1654:
1649:
1644:
1639:
1634:
1629:
1624:
1619:
1614:
1609:
1604:
1599:
1594:
1589:
1587:Pro-innovation
1584:
1579:
1574:
1572:Overton window
1569:
1564:
1559:
1554:
1549:
1544:
1539:
1534:
1529:
1524:
1519:
1514:
1509:
1504:
1499:
1494:
1489:
1484:
1479:
1474:
1469:
1464:
1459:
1454:
1453:
1452:
1442:
1440:Dunning–Kruger
1437:
1432:
1427:
1422:
1417:
1412:
1411:
1410:
1400:
1395:
1390:
1385:
1380:
1379:
1378:
1368:
1363:
1358:
1357:
1356:
1354:Correspondence
1351:
1349:Actor–observer
1341:
1336:
1331:
1326:
1321:
1315:
1313:
1308:
1305:
1304:
1297:
1296:
1289:
1282:
1274:
1267:
1266:
1247:(1): 153–161.
1231:
1203:
1174:(2): c94–c99.
1154:
1097:
1046:
1039:
1021:
966:
896:
852:
821:
814:
796:
753:
723:
716:
696:
652:
637:
586:
565:(2): 103–115.
545:
533:
521:
509:
496:
494:
491:
489:
488:
482:
476:
470:
464:
458:
455:Reporting bias
452:
446:
440:
434:
428:
422:
419:Cherry picking
416:
410:
403:
401:
398:
397:
396:
393:
387:
380:reporting bias
368:
367:Related issues
365:
337:
334:
328:
327:Volunteer bias
325:
299:
296:
254:Attrition bias
250:
247:
246:
245:
238:
235:
222:
219:
218:
217:
216:
215:
208:
197:Cherry picking
188:
183:
180:
179:
178:
177:
176:
170:
160:
153:postmenopausal
139:
136:
135:
134:
119:
114:
111:
107:lead time bias
99:self-selection
56:
53:
51:
48:
31:Selection bias
26:
9:
6:
4:
3:
2:
2546:
2535:
2532:
2530:
2527:
2525:
2522:
2520:
2517:
2516:
2514:
2499:
2498:
2494:
2492:
2491:
2487:
2485:
2484:
2480:
2479:
2476:
2470:
2467:
2465:
2462:
2460:
2457:
2455:
2452:
2450:
2447:
2446:
2444:
2440:
2434:
2431:
2429:
2428:Meta-analysis
2426:
2424:
2421:
2419:
2416:
2414:
2411:
2410:
2408:
2406:
2402:
2396:
2395:Vaccine trial
2393:
2391:
2390:Seeding trial
2388:
2386:
2383:
2381:
2378:
2376:
2373:
2371:
2368:
2366:
2363:
2361:
2358:
2357:
2355:
2351:
2343:
2339:
2335:
2331:
2327:
2323:
2319:
2315:
2311:
2307:
2305:
2301:
2297:
2293:
2289:
2285:
2281:
2279:
2275:
2271:
2267:
2263:
2259:
2255:
2251:
2247:
2243:
2241:
2237:
2233:
2229:
2225:
2221:
2217:
2213:
2211:
2207:
2204:
2202:
2198:
2192:
2189:
2187:
2184:
2182:
2179:
2176:
2172:
2169:
2165:
2162:
2160:
2159:Retrospective
2157:
2156:
2155:
2152:
2150:
2146:
2142:
2139:
2138:
2136:
2133:
2128:
2124:
2116:
2113:
2112:
2111:
2108:
2104:
2101:
2099:
2096:
2094:
2091:
2090:
2089:
2086:
2085:
2083:
2080:
2079:EBM I to II-1
2075:
2071:
2065:
2062:
2060:
2057:
2055:
2052:
2050:
2047:
2045:
2042:
2038:
2035:
2033:
2030:
2029:
2028:
2025:
2024:
2022:
2018:
2014:
2010:
2003:
1998:
1996:
1991:
1989:
1984:
1983:
1980:
1968:
1965:
1963:
1959:
1958:
1955:
1949:
1946:
1944:
1941:
1939:
1936:
1935:
1933:
1929:
1923:
1920:
1918:
1915:
1913:
1910:
1908:
1905:
1903:
1900:
1896:
1893:
1891:
1888:
1886:
1885:United States
1883:
1881:
1878:
1876:
1873:
1871:
1868:
1866:
1863:
1861:
1860:False balance
1858:
1857:
1856:
1853:
1851:
1848:
1846:
1843:
1841:
1838:
1836:
1833:
1831:
1828:
1826:
1823:
1821:
1818:
1816:
1815:
1811:
1809:
1806:
1804:
1801:
1800:
1798:
1794:
1788:
1785:
1783:
1780:
1778:
1775:
1773:
1770:
1768:
1765:
1763:
1760:
1758:
1755:
1753:
1750:
1748:
1745:
1743:
1740:
1738:
1735:
1733:
1732:Participation
1730:
1728:
1725:
1723:
1720:
1718:
1715:
1713:
1710:
1708:
1705:
1701:
1700:Psychological
1698:
1697:
1696:
1693:
1691:
1688:
1686:
1683:
1681:
1678:
1677:
1675:
1673:
1669:
1663:
1660:
1658:
1655:
1653:
1650:
1648:
1645:
1643:
1640:
1638:
1635:
1633:
1630:
1628:
1625:
1623:
1620:
1618:
1615:
1613:
1610:
1608:
1605:
1603:
1600:
1598:
1595:
1593:
1590:
1588:
1585:
1583:
1580:
1578:
1575:
1573:
1570:
1568:
1565:
1563:
1560:
1558:
1555:
1553:
1550:
1548:
1545:
1543:
1540:
1538:
1535:
1533:
1530:
1528:
1525:
1523:
1520:
1518:
1515:
1513:
1510:
1508:
1505:
1503:
1500:
1498:
1495:
1493:
1490:
1488:
1485:
1483:
1480:
1478:
1475:
1473:
1470:
1468:
1467:Fading affect
1465:
1463:
1460:
1458:
1455:
1451:
1448:
1447:
1446:
1443:
1441:
1438:
1436:
1433:
1431:
1428:
1426:
1423:
1421:
1418:
1416:
1413:
1409:
1406:
1405:
1404:
1401:
1399:
1396:
1394:
1391:
1389:
1386:
1384:
1381:
1377:
1374:
1373:
1372:
1369:
1367:
1364:
1362:
1359:
1355:
1352:
1350:
1347:
1346:
1345:
1342:
1340:
1337:
1335:
1332:
1330:
1327:
1325:
1322:
1320:
1317:
1316:
1314:
1311:
1306:
1302:
1295:
1290:
1288:
1283:
1281:
1276:
1275:
1272:
1262:
1258:
1254:
1250:
1246:
1242:
1235:
1220:
1216:
1210:
1208:
1199:
1195:
1191:
1187:
1182:
1177:
1173:
1169:
1165:
1158:
1150:
1146:
1142:
1138:
1133:
1128:
1124:
1120:
1117:(7069): 754.
1116:
1112:
1108:
1101:
1093:
1089:
1085:
1081:
1077:
1073:
1069:
1065:
1061:
1057:
1056:Risk Analysis
1050:
1042:
1036:
1032:
1025:
1017:
1013:
1009:
1005:
1001:
997:
993:
989:
985:
981:
977:
970:
962:
958:
953:
948:
944:
940:
935:
930:
926:
922:
919:(7): e67912.
918:
914:
910:
903:
901:
892:
888:
883:
878:
874:
870:
866:
859:
857:
848:
844:
840:
836:
835:Technometrics
832:
825:
817:
811:
807:
800:
792:
788:
784:
780:
776:
772:
768:
764:
757:
749:
745:
741:
737:
730:
728:
719:
713:
709:
708:
700:
692:
688:
683:
678:
674:
670:
663:
656:
648:
644:
640:
634:
630:
626:
621:
616:
611:
606:
599:
598:
590:
582:
578:
573:
568:
564:
560:
556:
549:
542:
537:
530:
525:
518:
513:
506:
501:
497:
486:
483:
480:
477:
474:
471:
468:
465:
462:
461:Sampling bias
459:
456:
453:
450:
447:
444:
441:
438:
435:
432:
429:
426:
423:
420:
417:
414:
411:
408:
405:
404:
394:
391:
388:
385:
384:meta-analyses
381:
377:
374:
373:
372:
364:
361:
359:
355:
351:
347:
343:
333:
324:
322:
317:
312:
311:is required.
310:
305:
295:
293:
289:
287:
283:
279:
275:
274:response rate
271:
267:
263:
259:
255:
243:
239:
236:
233:
229:
228:meta-analysis
225:
224:
213:
209:
206:
202:
198:
195:
194:
192:
189:
186:
185:
174:
171:
168:
164:
161:
158:
154:
150:
147:
146:
145:
142:
141:
132:
128:
124:
120:
117:
116:
113:Time interval
110:
108:
104:
100:
95:
92:
88:
83:
81:
77:
73:
69:
68:biased sample
65:
64:random sample
61:
60:Sampling bias
55:Sampling bias
50:Types of bias
47:
45:
41:
36:
32:
19:
2495:
2488:
2481:
2448:
2270:Hazard ratio
2154:Cohort study
1845:In education
1812:
1796:Other biases
1782:Verification
1767:Survivorship
1746:
1717:Non-response
1690:Healthy user
1632:Substitution
1607:Self-serving
1403:Confirmation
1371:Availability
1319:Acquiescence
1244:
1241:Econometrica
1240:
1234:
1223:. Retrieved
1221:. 2017-11-17
1218:
1171:
1167:
1157:
1114:
1110:
1100:
1059:
1055:
1049:
1030:
1024:
983:
979:
969:
916:
912:
875:(1): 87–88.
872:
868:
838:
834:
824:
805:
799:
769:(3): 250–8.
766:
762:
756:
739:
735:
706:
699:
672:
668:
655:
596:
589:
562:
558:
548:
536:
524:
512:
500:
431:Funding bias
370:
362:
357:
353:
339:
330:
316:impact event
313:
304:Nick Bostrom
302:Philosopher
301:
290:
286:intervention
281:
277:
269:
265:
262:failure bias
253:
252:
172:
162:
148:
143:
96:
84:
79:
58:
39:
30:
29:
2464:Null result
2423:Replication
2318:Infectivity
2240:Association
2191:Case report
2181:Case series
2164:Prospective
1912:Publication
1865:Vietnam War
1712:Length time
1695:Information
1637:Time-saving
1497:Horn effect
1487:Halo effect
1435:Distinction
1344:Attribution
1339:Attentional
675:: 103–126.
270:nonresponse
242:data dredge
2513:Categories
2266:Odds ratio
2258:Risk ratio
2224:Prevalence
2210:Occurrence
2186:Case study
1875:South Asia
1850:Liking gap
1662:In animals
1627:Status quo
1542:Negativity
1445:Egocentric
1420:Congruence
1398:Commitment
1388:Blind spot
1376:Mean world
1366:Automation
1225:2020-10-29
980:The Lancet
841:(1): 1–3.
736:Cancer Res
493:References
358:unobserved
354:unobserved
350:regression
336:Mitigation
278:withdrawal
230:(see also
76:population
2326:Morbidity
2314:Virulence
2216:Incidence
1943:Debiasing
1922:White hat
1917:Reporting
1830:Inductive
1747:Selection
1707:Lead time
1680:Estimator
1657:Zero-risk
1622:Spotlight
1602:Restraint
1592:Proximity
1577:Precision
1537:Narrative
1492:Hindsight
1477:Frequency
1457:Emotional
1430:Declinism
1361:Authority
1334:Anchoring
1324:Ambiguity
1190:1660-2110
1000:0140-6736
943:1932-6203
677:CiteSeerX
615:CiteSeerX
610:0805.2775
346:exogenous
249:Attrition
2490:Glossary
2483:Category
2360:In vitro
2201:Measures
2020:Overview
1840:Inherent
1803:Academic
1777:Systemic
1762:Spectrum
1742:Sampling
1722:Observer
1685:Forecast
1597:Response
1557:Optimism
1552:Omission
1547:Normalcy
1517:In-group
1512:Implicit
1425:Cultural
1329:Affinity
1198:20407272
1141:16341005
1084:20626690
1016:27683727
961:23874465
913:PLOS ONE
891:15649954
791:25648490
783:17245804
400:See also
212:outliers
191:Post hoc
138:Exposure
127:variance
2365:In vivo
1962:General
1960:Lists:
1895:Ukraine
1820:Funding
1582:Present
1567:Outcome
1472:Framing
1261:1912352
1149:4390013
1119:Bibcode
1092:6485564
1064:Bibcode
1008:4164620
952:3706448
921:Bibcode
581:9504213
272:(lower
266:dropout
221:Studies
167:lagging
123:ethical
33:is the
1967:Memory
1880:Sweden
1870:Norway
1737:Recall
1507:Impact
1383:Belief
1301:Biases
1259:
1196:
1188:
1147:
1139:
1111:Nature
1090:
1082:
1037:
1014:
1006:
998:
959:
949:
941:
889:
812:
789:
781:
748:698947
746:
714:
679:
647:842488
645:
635:
617:
579:
2304:Other
1855:Media
1825:FUTON
1257:JSTOR
1145:S2CID
1088:S2CID
1012:S2CID
787:S2CID
665:(PDF)
643:S2CID
605:arXiv
601:(PDF)
74:of a
2143:vs.
2011:and
1194:PMID
1186:ISSN
1137:PMID
1080:PMID
1035:ISBN
1004:PMID
996:ISSN
957:PMID
939:ISSN
887:PMID
810:ISBN
779:PMID
744:PMID
712:ISBN
633:ISBN
577:PMID
280:and
182:Data
131:mean
35:bias
1902:Net
1787:Wet
1249:doi
1176:doi
1172:115
1127:doi
1115:438
1072:doi
988:doi
984:289
947:PMC
929:doi
877:doi
843:doi
771:doi
687:doi
673:519
625:doi
567:doi
378:or
276:),
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