MODELS FOR ESTIMATING THE NUMBER OF UNPUBLISHED STUDIES

✍ Scribed by LEON J. GLESER; INGRAM OLKIN

• Book ID: 102651322
• Publisher: John Wiley and Sons
• Year: 1996
• Tongue: English
• Weight: 938 KB
• Volume: 15
• Category: Article
• ISSN: 0277-6715
• DOI: 10.1002/(sici)1097-0258(19961215)15:23<2493::aid-sim381>3.0.co;2-c

✦ Synopsis

The possible existence of unreported studies can cast doubt on the conclusions of a meta-analytic summary of the literature, particularly if there is reason to believe that there is a publication bias against non-significant results. The present article proposes two general models that describe how the preponderance of published studies could report significant p-values even when testing a null hypothesis that is, in fact, true. Each such model allows one to estimate the number, N , of unpublished studies using the p-values reported in the published studies; the meta-analyst can then evaluate the plausibility of this estimated value of N , or related confidence bounds. Use of models of the kind suggested here allows meta-analysts to assess the problem of unpublished studies from various perspectives and thus can lead to greater understanding of, and confidence in, meta-analytic conclusions.