Bayesian meta-analysis for longitudinal data models using multivariate mixture priors

Biometrics

Volumn 59, Issue 1, 2003, Pages 66-75

  Lopes, Hedibert Freitas ^a   Müller, Peter ^b   Rosner, Gary L ^b  

^a FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

Author keywords

Markov chain Monte Carlo; Mixture model; Model averaging; Model selection; Pharmacodynamic models; Reversible jump

Indexed keywords

DISEASES; HIERARCHICAL SYSTEMS; PATIENT TREATMENT;

LONGITUDINAL DATA; MARKOV CHAIN MONTE CARLO; MARKOV CHAIN MONTE-CARLO; META-ANALYSIS; MIXTURE MODELING; MODEL AVERAGING; MODEL SELECTION; PHARMACODYNAMIC MODELS; RANDOM EFFECTS; REVERSIBLE JUMP;

MARKOV PROCESSES;

AMIFOSTINE; CYCLOPHOSPHAMIDE; GRANULOCYTE MACROPHAGE COLONY STIMULATING FACTOR;

BAYESIAN ANALYSIS; BIOMETRY; META-ANALYSIS;

ARTICLE; BAYES THEOREM; BIOSTATISTICS; BONE MARROW SUPPRESSION; BONE MARROW TOXICITY; CANCER CHEMOTHERAPY; CLINICAL TRIAL; DATA ANALYSIS; HUMAN; LEUKOCYTE COUNT; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; META ANALYSIS; MULTIVARIATE ANALYSIS; PHARMACODYNAMICS; PHASE 1 CLINICAL TRIAL; PROBABILITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; TREATMENT OUTCOME;

EID: 0037367594     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/1541-0420.00008     Document Type: Article

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