ArticleJournal of the American Statistical Association2015
Bayesian Inference for Multivariate Meta-regression with a Partially Observed Within-Study Sample Covariance Matrix.
Article in Journal of the American Statistical Association, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Bayesian Joint Modeling of Response Times with Dynamic Latent Ability in Educational Testing.Psychometrika · 2025Article
- Multivariate meta-analysis with a robustified diagonal likelihood function.Journal of applied statistics · 2025Article
- metapack: An R Package for Bayesian Meta-Analysis and Network Meta-Analysis with a Unified Formula Interface.The R journal · 2022Article
- Bayesian network meta-regression hierarchical models using heavy-tailed multivariate random effects with covariate-dependent variances.Statistics in medicine · 2021Article
- Do the combined blood pressure effects of exercise and antihypertensive medications add up to the sum of their parts? A systematic meta-review.BMJ open sport & exercise medicine · 2021Review
- Bayesian Meta-Regression Model Using Heavy-Tailed Random-effects with Missing Sample Sizes for Self-thinning Meta-data.Statistics and its interface · 2020Article
- Bayesian inference for network meta-regression using multivariate random effects with applications to cholesterol lowering drugs.Biostatistics (Oxford, England) · 2019Article
- Bayesian Modeling and Inference for Nonignorably Missing Longitudinal Binary Response Data with Applications to HIV Prevention Trials.Statistica Sinica · 2018Article
- An improved method for bivariate meta-analysis when within-study correlations are unknown.Research synthesis methods · 2018Article
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Authors and funding
6 authors.
Funding
Abstract
Multivariate meta-regression models are commonly used in settings where the response variable is naturally multi-dimensional. Such settings are common in cardiovascular and diabetes studies where the goal is to study cholesterol levels once a certain medication is given. In this setting, the natural multivariate endpoint is Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). In this paper, we examine study level (aggregate) multivariate meta-data from 26 Merck sponsored double-blind, randomized, active or placebo-controlled clinical trials on adult patients with primary hypercholesterolemia. Our goal is to develop a methodology for carrying out Bayesian inference for multivariate meta-regression models with study level data when the within-study sample covariance matrix
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Registered trials
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