Literature DB >> 21506942

Testing overall and moderator effects in random effects meta-regression.

Hilde M Huizenga1, Ingmar Visser, Conor V Dolan.   

Abstract

Random effects meta-regression is a technique to synthesize results of multiple studies. It allows for a test of an overall effect, as well as for tests of effects of study characteristics, that is, (discrete or continuous) moderator effects. We describe various procedures to test moderator effects: the z, t, likelihood ratio (LR), Bartlett-corrected LR (BcLR), and resampling tests. We compare the Type I error of these tests, and conclude that the common z test, and to a lesser extent the LR test, do not perform well since they may yield Type I error rates appreciably larger than the chosen alpha. The error rate of the resampling test is accurate, closely followed by the BcLR test. The error rate of the t test is less accurate but arguably tolerable. With respect to statistical power, the BcLR and t tests slightly outperform the resampling test. Therefore, our recommendation is to use either the resampling or the BcLR test. If these statistics are unavailable, then the t test should be used since it is certainly superior to the z test.

Mesh:

Year:  2011        PMID: 21506942     DOI: 10.1348/000711010X522687

Source DB:  PubMed          Journal:  Br J Math Stat Psychol        ISSN: 0007-1102            Impact factor:   3.380


  28 in total

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6.  Elevated Serum Levels of NSE and S-100β Correlate with Increased Risk of Acute Cerebral Infarction in Asian Populations.

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8.  Adiponectin Gene Polymorphisms are Associated with Increased Risk of Colorectal Cancer.

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Journal:  Med Sci Monit       Date:  2015-09-02

9.  Estimated HIV Incidence in California, 2006-2009.

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Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

10.  Predictive Performance of Serum β-hCG MoM Levels for Preeclampsia Screening: A Meta-Analysis.

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Journal:  Front Endocrinol (Lausanne)       Date:  2021-06-10       Impact factor: 5.555

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