Comments about joint modeling of cluster size and binary and continuous subunit-specific outcomes

Biometrics

Volumn 61, Issue 3, 2005, Pages 862-866

  Gueorguieva, Ralitza V ^a   Chen, Zhen ^b   Dunson, David B ^c  

^a YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

Author keywords

Developmental toxicity; Maximum likelihood; PROC NLMIXED; Repeated measures

Indexed keywords

CLUSTER ANALYSIS; MAXIMUM LIKELIHOOD ESTIMATION; RANDOM PROCESSES; TOXICITY;

BAYESIAN APPROACHES; CLUSTER SIZES; DEVELOPMENTAL TOXICITY; JOINT MODELS; LONGITUDINAL STUDY; MA XIMUM LIKELIHOODS; MAXIMUM-LIKELIHOOD; PROC NLMIXED; REPEATED MEASURES; TOXICITY DATA;

BAYESIAN NETWORKS;

MAXIMUM LIKELIHOOD ANALYSIS; STATISTICAL ANALYSIS; TOXICITY;

CLUSTER ANALYSIS; COMPUTER PROGRAM; EPIDEMIOLOGY; OUTCOMES RESEARCH; RANDOMIZATION; REVIEW; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; ANIMAL; BAYES THEOREM; BIOLOGICAL MODEL; EMBRYO DEVELOPMENT; FEMALE; METABOLISM; MOUSE; NOTE; PREGNANCY;

ETHYLENE GLYCOL;

ANIMALS; BAYES THEOREM; CLUSTER ANALYSIS; EMBRYONIC DEVELOPMENT; ETHYLENE GLYCOL; FEMALE; MICE; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PREGNANCY; SOFTWARE;

EID: 27744550306     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1541-020X.2005.00409_1.x     Document Type: Review

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