The alternative regression test has comparable power to Egger's regression test to detect publication bias under conditions of low between-study heterogeneity.Ĭonclusion Because of appropriate type I error rates and reduction in the correlation between the lnOR and its variance, the alternative regression test can be used in place of Egger's regression test when the summary estimates are lnORs.
The alternative regression test has the appropriate type I error rates regardless of the size of the underlying OR, the number of primary studies in the meta-analysis, and the level of between-study heterogeneity. Results Type I error rates for Egger's regression test are higher than those for the alternative regression test. Main Outcome Measures Type I error rates (the proportion of false-positive results) for each regression test and their power to detect publication bias when it is present (the proportion of true-positive results). Objective To compare the performance of Egger's regression test with a regression test based on sample size (a modification of Macaskill's test) with lnOR as the summary estimate.ĭesign Simulation of meta-analyses under a number of scenarios in the presence and absence of publication bias and between-study heterogeneity. However, the performance of this test and the usual funnel plot have been challenged particularly when the summary estimate is the natural log of the odds ratio (lnOR). Shared Decision Making and CommunicationĬontext Egger's regression test is often used to help detect publication bias in meta-analyses.Scientific Discovery and the Future of Medicine.Health Care Economics, Insurance, Payment.Clinical Implications of Basic Neuroscience.Challenges in Clinical Electrocardiography.
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