Multiple Imputation for Missing Values through Conditional Semiparametric Odds Ratio Models

DOI10.1111/j.1541-0420.2010.01538.xzbMath1226.62020OpenAlexW2085772009WikidataQ42803785 ScholiaQ42803785MaRDI QIDQ3100780

Yi Qian, Hui Xie, Hua Yun Chen

Publication date: 21 November 2011

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3135790

zbMATH Keywords

Gibbs samplerDirichlet process priornonparametric Bayesian inferenceacceptance-rejection samplingmolecular dynamics algorithmhybrid MCMCrejection control

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Parametric inference (62F99) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (3)

Diagnostic checking of multiple imputation models ⋮ Unified approach for regression models with nonmonotone missing at random data ⋮ Semiparametric model for regression analysis with nonmonotone missing data

Cites Work

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• Inferences on missing information under multiple imputation and two-stage multiple imputation
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Ferguson distributions via Polya urn schemes
• Nonparametric Bayesian data analysis
• Prior distributions on spaces of probability measures
• Markov chains for exploring posterior distributions. (With discussion)
• A Bayesian analysis of some nonparametric problems
• Multiple Imputation After 18+ Years
• Inference and missing data
• Bayesian Nonparametric Inference for Random Distributions and Related Functions
• Sequential importance sampling for nonparametric Bayes models: The next generation
• Estimating Normal Means with a Dirichlet Process Prior
• Nonparametric and Semiparametric Models for Missing Covariates in Parametric Regression
• A Note on the Prospective Analysis of Outcome-Dependent Samples
• Multiple imputation: current perspectives
• Multiple imputation of discrete and continuous data by fully conditional specification
• Evaluation of software for multiple imputation of semi-continuous data
• A Semiparametric Odds Ratio Model for Measuring Association
• Contemporary Bayesian Econometrics and Statistics
• Missing-Data Methods for Generalized Linear Models
• Monte Carlo strategies in scientific computing

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