Bayesian approach to joint analysis of longitudinal measurements and competing risks failure time data

Statistics in Medicine

Volumn 28, Issue 11, 2009, Pages 1601-1619

  Hu, Wenhua ^a   Li, Gang ^b   Li, Ning ^c  

^a BRISTOL MYERS SQUIBB   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF FLORIDA   (United States)

Author keywords

Bayesian approach; Competing risks; Joint modeling; Longitudinal data

Indexed keywords

CYCLOPHOSPHAMIDE; PLACEBO;

ACCURACY; ARTICLE; BAYES THEOREM; CALCULATION; CONFIDENCE INTERVAL; CONTROLLED STUDY; COVARIANCE; DATA ANALYSIS; DOSE RESPONSE; DRUG DOSE INCREASE; DRUG WITHDRAWAL; EVALUATION; FORCED EXPIRATORY VOLUME; HUMAN; INTERMETHOD COMPARISON; INTERSTITIAL LUNG DISEASE; LONGITUDINAL STUDY; LUNG ALVEOLITIS; LUNG DISEASE; LUNG FIBROSIS; MATHEMATICAL COMPUTING; MATHEMATICAL VARIABLE; MAXIMUM LIKELIHOOD METHOD; MEASUREMENT ERROR; MONTE CARLO METHOD; MORTALITY; NORMAL DISTRIBUTION; PROBABILITY; PROCESS DEVELOPMENT; PROCESS MODEL; SAMPLE SIZE; SAMPLING; SCLERODERMA; STATISTICAL ANALYSIS; STATISTICAL MODEL; SURVIVAL; TREATMENT FAILURE; UNSPECIFIED SIDE EFFECT; ALGORITHM; COMPARATIVE STUDY; FOLLOW UP; PROPORTIONAL HAZARDS MODEL; RANDOMIZED CONTROLLED TRIAL; RISK ASSESSMENT; RISK FACTOR; TIME; TREATMENT OUTCOME;

ALGORITHMS; BAYES THEOREM; FOLLOW-UP STUDIES; HUMANS; LIKELIHOOD FUNCTIONS; LINEAR MODELS; LONGITUDINAL STUDIES; LUNG DISEASES, INTERSTITIAL; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; PROPORTIONAL HAZARDS MODELS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; RISK ASSESSMENT; RISK FACTORS; TIME FACTORS; TREATMENT FAILURE; TREATMENT OUTCOME;

EID: 67649945929     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3562     Document Type: Article

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