Empirical Comparison of Publication Bias Tests in Meta-Analysis.

ABSTRACT:

Background

Decision makers rely on meta-analytic estimates to trade off benefits and harms. Publication bias impairs the validity and generalizability of such estimates. The performance of various statistical tests for publication bias has been largely compared using simulation studies and has not been systematically evaluated in empirical data.

Methods

This study compares seven commonly used publication bias tests (i.e., Begg's rank test, trim-and-fill, Egger's, Tang's, Macaskill's, Deeks', and Peters' regression tests) based on 28,655 meta-analyses available in the Cochrane Library.

Results

Egger's regression test detected publication bias more frequently than other tests (15.7% in meta-analyses of binary outcomes and 13.5% in meta-analyses of non-binary outcomes).

SUBMITTER: Lin L 

PROVIDER: S-EPMC6082203 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature