A Bayesian Hierarchical Model for Categorical Data with Nonignorable Nonresponse

Biometrics

Volumn 59, Issue 4, 2003, Pages 886-896

  Green, Paul E ^a   Park, Taesung ^b  

^a UNIVERSITY OF MICHIGAN SCHOOL OF PUBLIC HEALTH   (United States)

^b Seoul National University   (South Korea)

Author keywords

MCMC simulation; Nonignorable missing data; Variable selection

Indexed keywords

BAYESIAN NETWORKS; CREATININE; HIERARCHICAL SYSTEMS; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; REGRESSION ANALYSIS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

BAYESIAN HIERARCHICAL MODELLING; DATA TABLES; LOGLINEAR MODEL; MARKOV CHAIN MONTE CARLO SIMULATION; MISSING DATA; NONIGNORABLE MISSING DATA; NONIGNORABLE NONRESPONSE; SELECTION PROCEDURES; STOCHASTIC SEARCH; VARIABLES SELECTIONS;

PARKS;

BAYESIAN ANALYSIS;

ARTICLE; BAYES THEOREM; DATA ANALYSIS; MAXIMUM LIKELIHOOD METHOD; PROBABILITY; STATISTICAL ANALYSIS; STOCHASTIC MODEL;

EID: 0346733307     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2003.00103.x     Document Type: Article

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