On tests of the overall treatment effect in meta‐analysis with normally distributed responses
Top Cited Papers
- 30 May 2001
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 20 (12) , 1771-1782
- https://doi.org/10.1002/sim.791
Abstract
For the meta‐analysis of controlled clinical trials or epidemiological studies, in which the responses are at least approximately normally distributed, a refined test for the hypothesis of no overall treatment effect is proposed. The test statistic is based on a direct estimation function for the variance of the overall treatment effect estimator. As outcome measures, the absolute and the standardized difference between means are considered. In simulation studies it is shown that the proposed test keeps the prescribed significance level very well in contrast to the commonly used tests in the fixed effects and random effects model, respectively, which can become very liberal. Furthermore, just for using the proposed test it is not necessary to choose between the fixed effects and the random effects approach in advance. Copyright © 2001 John Wiley & Sons, Ltd.Keywords
This publication has 11 references indexed in Scilit:
- Explaining heterogeneity in meta-analysis: a comparison of methodsStatistics in Medicine, 1999
- Detecting and describing heterogeneity in meta-analysisStatistics in Medicine, 1998
- INCORPORATING VARIABILITY IN ESTIMATES OF HETEROGENEITY IN THE RANDOM EFFECTS MODEL IN META-ANALYSISStatistics in Medicine, 1997
- A LIKELIHOOD APPROACH TO META-ANALYSIS WITH RANDOM EFFECTSStatistics in Medicine, 1996
- A random‐effects regression model for meta‐analysisStatistics in Medicine, 1995
- The bias of the commonly-used estimate of variance in meta-analysisCommunications in Statistics - Theory and Methods, 1994
- A general parametric approach to the meta‐analysis of randomized clinical trialsStatistics in Medicine, 1991
- Meta-analysis in clinical trialsControlled Clinical Trials, 1986
- Nonnegative Minimum Biased Invariant Estimation in Variance Component ModelsThe Annals of Statistics, 1981
- Estimation of Variance and Covariance Components in Linear ModelsJournal of the American Statistical Association, 1972