Mixed effects logistic regression models for multiple longitudinal binary functional limitation responses with informative drop-out and confounding by baseline outcomes

Biometrics

Volumn 58, Issue 1, 2002, Pages 137-144

  Ten Have, T R ^a   Reboussin, B A ^b   Miller, M E ^b   Kunselman, A ^c  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b WAKE FOREST SCHOOL OF MEDICINE   (United States)

^c PENN STATE COLLEGE OF MEDICINE   (United States)

Author keywords

Autoregressive structure; Discrete time survival; Nested random effects; Numerical integration; Shared parameter

Indexed keywords

DROPS; MAXIMUM LIKELIHOOD ESTIMATION; REGRESSION ANALYSIS;

AUTO-REGRESSIVE; AUTOREGRESSIVE STRUCTURE; DISCRETE TIME; DISCRETE-TIME SURVIVAL; DROP-OUT; LONGITUDINAL STUDY; NESTED RANDOM EFFECT; NUMERICAL INTEGRATIONS; RANDOM EFFECTS; SHARED PARAMETER;

RANDOM PROCESSES;

AGING; MEDICAL GEOGRAPHY; REGRESSION ANALYSIS;

AGING; ARTICLE; HUMAN; LOGISTIC REGRESSION ANALYSIS; MAXIMUM LIKELIHOOD METHOD; OUTCOMES RESEARCH; PREDICTION; STATISTICAL MODEL; SURVIVAL TIME;

EID: 0036191541     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2002.00137.x     Document Type: Article

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