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[Gibbs-Sampler approach for meta-analysis of multiple clinical trials using generalized linear model with random-effects].

Abstract：

OBJECTIVE:To investigate the use of the Gibbs-Sampler method in evaluating the relationship between clinic events and health risks in a meta-analysis of multiple clinical trials. METHODS:By using a generalized linear model with random-effects, Gibbs-Sampler technique was used in a meta-analysis of multiple clinical trials of angiotensin converting enzyme (ACE) inhibitors in patients with myocardial infarction (MI). RESULTS:When heterogeneity across different trials can not be ignored, compared with the classic method, the odds ratio of relative reinfarction risk estimated by the Gibbs-Sampler method would have less variation. The gain in the reduction of variation in estimate of the overall odds ratio was 9.52%. CONCLUSION:Implementation of the Gibbs-Sampler technique in meta-analysis of multiple clinical trials has the potential of reducing the inaccuracy caused by heterogeneity across trials.

journal_name

Chin Med J (Engl)

journal_title

Chinese medical journal

authors

Wang Y,Wang Y,Li L,Wang Z,Macus F,Salim Y

keywords:

subject

Has Abstract

pub_date

2000-06-01 00:00:00

pages

554-7

issue

6

eissn

0366-6999

issn

2542-5641

journal_volume

113

pub_type

杂志文章

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