Abstract
Background. Publication bias is a form of scientific misconduct. It threatens the validity of research results and the credibility of science. Although several tests on publication bias exist, no in-depth evaluations are available that examine which test performs best for different research settings. Methods. Four tests on publication bias, Egger's test (FAT), p-uniform, the test of excess significance (TES), as well as the caliper test, were evaluated in a Monte Carlo simulation. Two different types of publication bias and its degree (0%, 50%, 100%) were simulated. The type of publication bias was defined either as file-drawer, meaning the repeated analysis of new datasets, or p-hacking, meaning the inclusion of covariates in order to obtain a significant result. In addition, the underlying effect (beta = 0, 0.5, 1, 1.5), effect heterogeneity, the number of observations in the simulated primary studies (N = 100, 500), and the number of observations for the publication bias tests (K = 100, 1,000) were varied. Results. All tests evaluated were able to identify publication bias both in the filed raw er and p-hacking condition. The false positive rates were, with the exception of the 15%- and 20%-caliper test, unbiased. The FAT had the largest statistical power in the file-drawer conditions, whereas under p-hacking the TES was, except under effect heterogeneity, slightly better. The CTs were, however, inferior to the other tests under effect homogeneity and had a decent statistical power only in conditions with 1,000 primary studies. Discussion. The FAT is recommended as a test for publication bias in standard meta-analyses with no or only small effect heterogeneity. If two-sided publication bias is suspected as well as under p-hacking the TES is the first alternative to the FAT. The 5%-caliper test is recommended under conditions of effect heterogeneity and a large number of primary studies, which may be found if publication bias is examined in a discipline-wide setting when primary studies cover different research problems.
Dokumententyp: | Zeitschriftenartikel |
---|---|
Fakultät: | Sozialwissenschaften > Department: Institut für Soziologie |
Themengebiete: | 300 Sozialwissenschaften > 300 Sozialwissenschaft, Soziologie |
URN: | urn:nbn:de:bvb:19-epub-53397-9 |
ISSN: | 2167-8359 |
Sprache: | Englisch |
Dokumenten ID: | 53397 |
Datum der Veröffentlichung auf Open Access LMU: | 14. Jun. 2018, 09:52 |
Letzte Änderungen: | 04. Nov. 2020, 13:32 |