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A tutorial on Bayesian bivariate meta-analysis of mixed binary-continuous outcomes with missing treatment effects

机译:缺少治疗效果的混合二元连续结果的贝叶斯双变量荟萃分析指南

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摘要

Bivariate random-effects meta-analysis (BVMA) is a method of data synthesis that accounts for treatment effects measured on two outcomes. BVMA gives more precise estimates of the population mean and predicted values than two univariate random-effects meta-analyses (UVMAs). BVMA also addresses bias from incomplete reporting of outcomes.
机译:双变量随机效应荟萃分析(BVMA)是一种数据综合方法,考虑了在两种结果上测得的治疗效果。与两个单变量随机效应荟萃分析(UVMA)相比,BVMA可以更准确地估算总体平均值和预测值。 BVMA还解决了成果报告不完整带来的偏见。

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