Modeling publication bias using weighted distributions in a Bayesian framework.

DOI10.1016/S0167-9473(97)00039-XzbMath1042.62525MaRDI QIDQ1128453

Daniel T. Larose, Dey, Dipak K.

Publication date: 13 August 1998

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

Meta-analysisWeight functionMonte-Carlo estimationMarkov-chain Monte-CarloPublication biasSampling methods

Mathematics Subject Classification ID

Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (4)

A Bound for Publication Bias Based on the Fraction of Unpublished Studies ⋮ Modelling publication bias in meta-analysis: a review ⋮ Bayesian methods in meta-analysis and evidence synthesis ⋮ Assessing the Implications of Publication Bias for Two Popular Estimates of between‐Study Variance in Meta‐Analysis

Cites Work

• Inference from iterative simulation using multiple sequences
• Weighted distributions viewed in the context of model selection: A Bayesian perspective
• Sampling-Based Approaches to Calculating Marginal Densities
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Sampling and Bayes' Inference in Scientific Modelling and Robustness
• What Bayesians Expect of Each Other
• A Predictive Approach to Model Selection
• Bayesian Inference in Econometric Models Using Monte Carlo Integration
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