Publication bias

Publication bias, or the file-drawer effect, refers to the possibility of a systemic bias in published research in a field due to over-reporting of positive results. The reasons for this can be:

  • A positive result is usually seen as more interesting than a study that finds no effect. Thus, positive results will have a tendency to get published more often even if they may be spurious. Many peer-reviewed publications have to reject many otherwise high-quality studies and need to rank publications not only on scientific merit but on scientific importance; positive results may be one contributor to the perceived importance of a study.
  • The researcher, having found nothing, may simply be uninterested in writing up and reporting the results.
  • The researcher may have a self-interest against publishing negative results; for example, a curriculum vitae of published studies with many negative results is likely to be less promotion-worthy or grant-worthy than one with many positive results. A researcher might also have a financial interest in positive results, e.g. a study of a pharmaceutical in which the researcher is financially invested.
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A study of published and unpublished clinical trials found that positive results in the sample were three times more likely to be published.[1] Publication bias is known to be an issue with research funded by "Big Pharma" as pharmaceutical companies are often required to register their clinical trials in a public database but not required to actually report all the results, allowing them to inflate the perceived efficacy of treatments. A number of journals have been launched specifically for the purpose of reporting negative results in order to combat publication bias.[2] John Iaonnidis, a medical researcher, has provoked a substantial amount of academic debate with his claims that most published research is ultimately false.[3]

A secondary impact of publication bias is on review articles and meta-analyses. Both types of publications summarize the existing literature and, thus, rely on either the inclusion of all studies or, at the very least, for unpublished studies to be otherwise similar to published studies. If unpublished studies tend to be negative studies, publication bias further biases reviews and meta-analyses.

See also

References
  1. K. Dickerson et al. Publication Bias and Clinical Trials. Controlled Clinical Trials 8 (4): 343–353.
  2. Your Experiment Didn't Work Out? The Journal of Errology Wants to Hear From You, Retraction Watch
  3. John P.A. Iaonnidis. Why Most Published Research Findings Are False. PLoS Med. 2005 August; 2(8): e124.
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