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Yao, Minghong; Wang, Yuning; Ren, Yan; Jia, Yulong; Zou, Kang; Li, Ling; Sun, Xin – Research Synthesis Methods, 2023
Rare events meta-analyses of randomized controlled trials (RCTs) are often underpowered because the outcomes are infrequent. Real-world evidence (RWE) from non-randomized studies may provide valuable complementary evidence about the effects of rare events, and there is growing interest in including such evidence in the decision-making process.…
Descriptors: Evidence, Meta Analysis, Randomized Controlled Trials, Decision Making
Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2022
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…
Descriptors: Patients, Medical Research, Comparative Analysis, Outcomes of Treatment
Yamaguchi, Yusuke; Sakamoto, Wataru; Goto, Masashi; Staessen, Jan A.; Wang, Jiguang; Gueyffier, Francois; Riley, Richard D. – Research Synthesis Methods, 2014
When some trials provide individual patient data (IPD) and the others provide only aggregate data (AD), meta-analysis methods for combining IPD and AD are required. We propose a method that reconstructs the missing IPD for AD trials by a Bayesian sampling procedure and then applies an IPD meta-analysis model to the mixture of simulated IPD and…
Descriptors: Meta Analysis, Patients, Bayesian Statistics, Comparative Analysis
Lee, Sik-Yum; Xia, Ye-Mao – Psychometrika, 2008
In this paper, normal/independent distributions, including but not limited to the multivariate t distribution, the multivariate contaminated distribution, and the multivariate slash distribution, are used to develop a robust Bayesian approach for analyzing structural equation models with complete or missing data. In the context of a nonlinear…
Descriptors: Structural Equation Models, Bayesian Statistics, Evaluation Methods, Evaluation Research

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