Modeling disease-state transition heterogeneity through Bayesian variable selection

Statistics in Medicine

Volumn 28, Issue 9, 2009, Pages 1353-1368

  Healy, Brian C ^a   Engler, David ^b,c  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b BRIGHAM YOUNG UNIVERSITY   (United States)

^c Brigham Young University ^*  (United States)

Author keywords

Bayesian variable selection; Markov transition models; Multinomial logit models; Multiple sclerosis

Indexed keywords

ANALYSIS OF COVARIANCE; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; DATA ANALYSIS; DISEASE COURSE; DISEASE DURATION; HIDDEN MARKOV MODEL; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MULTIPLE SCLEROSIS; PHYSICAL DISABILITY; PROBABILITY; RELAPSE; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL SIGNIFICANCE; BIOMETRY; CLASSIFICATION; COMPUTER SIMULATION; DISABILITY; GENERAL ASPECTS OF DISEASE; HUMAN; PATHOPHYSIOLOGY; STATISTICAL MODEL; SYSTEM ANALYSIS;

BAYES THEOREM; BIOMETRY; COMPUTER SIMULATION; DISABILITY EVALUATION; DISEASE; HUMANS; MARKOV CHAINS; MODELS, STATISTICAL; MULTIPLE SCLEROSIS; PROBABILITY THEORY;

EID: 67549108378     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3545     Document Type: Article

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