Publication Bias
Publication bias occurs when the results of a study influence whether the study is published. Typically, studies with statistically significant or positive results are more likely to be published than studies with non-significant or negative results, even if both are scientifically valid. This bias distorts the published literature, making treatments appear more effective than they actually are. Rosenthal (1979) termed this the 'file drawer problem': research with null results sits in file drawers, unpublished, creating a biased sample of published evidence. Funnel plots and statistical tests (e.g., Egger test) can detect asymmetry suggesting publication bias; meta-analyses must account for this bias.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638–641. · DOI 10.1037/0033-2909.86.3.638
- Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634. · DOI 10.1136/bmj.315.7109.629
- Chan, A. W., Hrobjartsson, A., Haahr, M. T., Gøtzsche, P. C., & Altman, D. G. (2004). Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. JAMA, 291(20), 2457–2465. · DOI 10.1001/jama.291.20.2457
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.