We examine two strategies for meta-analysis of a series of 2;2 tables with the odds ratio modelled as a linear combination of study level covariates and random effects representing between-study variation. Penalized quasi-likelihood (PQL), an approximate inference technique for generalized linear mi
Meta-analysis by random effect modelling in generalized linear models
β Scribed by Murray Aitkin
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 94 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
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β¦ Synopsis
The meta-analysis of multi-centre trials can be based on either "xed or random e!ect models. This paper argues for the general use of random e!ect models, and illustrates the value of non-parametric maximum likelihood (NPML) analysis of such trials. The same general approach uni"es administrative &league table' analyses in epidemiological and other studies. Several examples of the NPML analysis are given, including a 70-centre trial.
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Meta-analysis refers to quantitative methods to combine results from independent studies so as to draw overall conclusions. Frequently, results from dissimilar studies are inappropriately combined, resulting in suspect inferential synthesis. We present a straightforward method to identify and addres
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When combining results from separate investigations in a meta-analysis, random effects methods enable the modelling of differences between studies by incorporating a heterogeneity parameter that accounts explicitly for across-study variation. We develop a simple form for the variance of Cochran's ho