The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Publication bias in psychological science: Prevalence, methods for identifying and controlling, and implications for the use of meta-analyses.
Abstract
The issue of publication bias in psychological science is one that has remained difficult to address despite decades of discussion and debate. The current article examines a sample of 91 recent meta-analyses published in American Psychological Association and Association for Psychological Science journals and the methods used in these analyses to identify and control for publication bias. Of the 91 studies analyzed, 64 (70%) made some effort to analyze publication bias, and 26 (41%) reported finding evidence of bias. Approaches to controlling publication bias were heterogeneous among studies. Of these studies, 57 (63%) attempted to find unpublished studies to control for publication bias. Nonetheless, those studies that included unpublished studies were just as likely to find evidence for publication bias as those that did not. Furthermore, authors of meta-analyses themselves were overrepresented in unpublished studies acquired, as compared with published studies, suggesting that searches for unpublished studies may increase rather than decrease some sources of bias. A subset of 48 meta-analyses for which study sample sizes and effect sizes were available was further analyzed with a conservative and newly developed tandem procedure of assessing publication bias. Results indicated that publication bias was worrisome in about 25% of meta-analyses. Meta-analyses that included unpublished studies were more likely to show bias than those that did not, likely due to selection bias in unpublished literature searches. Sources of publication bias and implications for the use of meta-analysis are discussed.
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Citations
Cites
A meta-analytic test of intergroup contact theory.
Pettigrew, T. F., & Tropp, L. R. (2006) · Journal of personality and social psychology · doi:10.1037/0022-3514.90.5.751 · Cited by 9,708
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068
Selective publication of antidepressant trials and its influence on apparent efficacy
Turner, E. H., Matthews, A. M., Linardatos, E., Tell, R. A., & Rosenthal, R. (2008) · New England Journal of Medicine · doi:10.1056/nejmsa065779 · Cited by 2,435
Publication Bias in Meta‐Analysis: Prevention, Assessment and Adjustments
(2005) · doi:10.1002/0470870168 · Cited by 2,368
Pharmaceutical industry sponsorship and research outcome and quality: systematic review
Lexchin, J., Bero, L. A., Djulbegovic, B., & Clark, O. (2003) · BMJ · doi:10.1136/bmj.326.7400.1167 · Cited by 2,147
Experimental disclosure and its moderators: A meta-analysis.
Frattaroli, J. (2006) · Psychological Bulletin · doi:10.1037/0033-2909.132.6.823 · Cited by 1,502
meta-analysis bias in location and selection of studies
Egger, M., & Smith, G. D. (1998) · BMJ · doi:10.1136/bmj.316.7124.61 · Cited by 1,374
A comparison of methods to detect publication bias in meta‐analysis
Macaskill, P., Walter, S. D., & Irwig, L. (2001) · Statistics in Medicine · doi:10.1002/sim.698 · Cited by 1,286
Peters, J. L., Sutton, A. J., Jones, D. R., Abrams, K. R., & Rushton, L. (2007) · Statistics in Medicine · doi:10.1002/sim.2889 · Cited by 716
Slavin, R. E. (2008) · Educational Researcher · doi:10.3102/0013189x08314117 · Cited by 560
Publication Bias in Research Synthesis: Sensitivity Analysis Using A Priori Weight Functions.
Vevea, J. L., & Woods, C. M. (2005) · Psychological Methods · doi:10.1037/1082-989x.10.4.428 · Cited by 461 · cited 1×
“There are sophisticated methods available for such analyses (e.g., Vevea & Woods, 2005), but the authors of the meta-analyses in our sample rarely used them (the rare exceptions were Pettigrew & Tropp, 2006; Shadish & Baldwin, 2005).”
MethodUsing Dissertations to Examine Potential Bias in Child and Adolescent Clinical Trials.
McLeod, B. D., & Weisz, J. R. (2004) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.72.2.235 · Cited by 125
Wilson, D. B. (2009) · Journal of Experimental Criminology · doi:10.1007/s11292-009-9085-5 · Cited by 86
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Siddaway, A. P., Wood, A. M., & Hedges, L. V. (2019) · Annual Review of Psychology · doi:10.1146/annurev-psych-010418-102803 · Cited by 2,550
Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies.
Sowislo, J. F., & Orth, U. (2013) · Psychological Bulletin · doi:10.1037/a0028931 · Cited by 2,123
The consequences of perceived discrimination for psychological well-being: A meta-analytic review.
Schmitt, M. T., Branscombe, N. R., Postmes, T., & Garcia, A. (2014) · Psychological Bulletin · doi:10.1037/a0035754 · Cited by 1,804
The effect of testing versus restudy on retention: A meta-analytic review of the testing effect.
Rowland, C. A. (2014) · Psychological Bulletin · doi:10.1037/a0037559 · Cited by 1,066
Lundahl, B., Moleni, T., Burke, B. L., Butters, R., Tollefson, D., Butler, C., & Rollnick, S. (2013) · Patient Education and Counseling · doi:10.1016/j.pec.2013.07.012 · Cited by 909
Metadata
- Authors
- Ferguson, C. J., & Brannick, M. T.
- Venue
- Psychological Methods
- Published
- 2012
- Volume
- 17
- Issue
- 1
- Pages
- 120-128
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2124519965
- Cited by
- 493
- References
- 13
- FWCI
- 24.99
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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