Joint modeling of longitudinal and survival data via a common frailty

Biometrics

Volumn 60, Issue 4, 2004, Pages 892-899

  Ratcliffe, Sarah J ^a   Guo, Wensheng ^a   Ten Have, Thomas R ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

EM algorithm; Frailty; Longitudinal data; Nonparametric maximum likelihood; Survival analysis

Indexed keywords

CLUSTERING ALGORITHMS; DISEASES; MAXIMUM LIKELIHOOD ESTIMATION; PATIENT TREATMENT; RANDOM PROCESSES;

EM ALGORITHMS; FRAILTY; JOINT MODELS; LONGITUDINAL DATA; MA XIMUM LIKELIHOODS; MAXIMUM-LIKELIHOOD; NONPARAMETRIC MAXIMUM LIKELIHOOD; NONPARAMETRICS; SURVIVAL ANALYSIS; SURVIVAL DATA;

CLUSTER ANALYSIS;

HEMOGLOBIN;

MODELING;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; COVARIANCE; DATA ANALYSIS; HEMODIALYSIS; HEMOGLOBIN DETERMINATION; HUMAN; KIDNEY FAILURE; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MAXIMUM LIKELIHOOD METHOD; NONPARAMETRIC TEST; STATISTICAL ANALYSIS; STATISTICAL MODEL; SURVIVAL TIME;

EID: 10944224477     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2004.00244.x     Document Type: Article

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