The magnitude of small-study effects in the Cochrane Database of Systematic Reviews: an empirical study of nearly 30 000 meta-analyses.

ABSTRACT: Publication bias, more generally termed as small-study effect, is a major threat to the validity of meta-analyses. Most meta-analysts rely on the p values from statistical tests to make a binary decision about the presence or absence of small-study effects. Measures are available to quantify small-study effects' magnitude, but the current literature lacks clear rules to help evidence users in judging whether such effects are minimal or substantial. This article aims to provide rules of thumb for interpreting the measures. We use six measures to evaluate small-study effects in 29 932 meta-analyses from the Cochrane Database of Systematic Reviews They include Egger's regression intercept and the skewness under both the fixed-effect and random-effects settings, the proportion of suppre

SUBMITTER: Lin L 

PROVIDER: S-EPMC6942244 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature