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Meta-analysis of Binary Data Using Profile Likelihood

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Meta-analysis of Binary Data Using Profile Likelihood

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Meta-analysis of Binary Data Using Profile Likelihood by Dankmar Bohning
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Description

Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies. Meta-Analysis of Binary Data Using Profile Likelihood focuses on the analysis and modeling of a meta-analysis with individually pooled data (MAIPD). It presents a unifying approach to modeling a treatment effect in a meta-analysis of clinical trials with binary outcomes. After illustrating the meta-analytic situation of an MAIPD with several examples, the authors introduce the profile likelihood model and extend it to cope with unobserved heterogeneity. They describe elements of log-linear modeling, ways for finding the profile maximum likelihood estimator, and alternative approaches to the profile likelihood method. The authors also discuss how to model covariate information and unobserved heterogeneity simultaneously and use the profile likelihood method to estimate odds ratios. The final chapters look at quantifying heterogeneity in an MAIPD and show how meta-analysis can be applied to the surveillance of scrapie. Containing new developments not available in the current literature, along with easy-to-follow inferences and algorithms, this book enables clinicians to efficiently analyze MAIPDs.
Release date NZ
April 8th, 2008
Country of Publication
United States
Illustrations
188 equations; 63 Tables, black and white; 54 Illustrations, black and white
Imprint
Chapman & Hall/CRC
Pages
208
Dimensions
156x235x18
ISBN-13
9781584886303
Product ID
2064934

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