A latent-class mixture model for incomplete longitudinal Gaussian data

Biometrics

Volumn 64, Issue 1, 2008, Pages 96-105

  Beunckens, Caroline ^a   Molenberghs, Geert ^a   Verbeke, Geert ^b   Mallinckrodt, Craig ^c  

^a HASSELT UNIVERSITY   (Belgium)

^b UNIVERSITY OF LEUVEN   (Belgium)

^c ELI LILLY AND COMPANY   (United States)

Author keywords

Latent class; Nonrandom missingness; Random effect; Shared parameter

Indexed keywords

MEDICAL APPLICATIONS; RANDOM PROCESSES;

CLINICAL TRIAL; GAUSSIAN DATA; LATENT CLASS; MISSING AT RANDOMS; MISSING NOT AT RANDOM; MIXTURE MODELING; NONRANDOM MISSINGNESS; RANDOM EFFECTS; SHARED PARAMETER; SIMPLE METHOD;

SENSITIVITY ANALYSIS;

ANTIDEPRESSANT AGENT;

GAUSSIAN METHOD; RANDOM WALK METHOD; SENSITIVITY ANALYSIS;

ALGORITHM; ARTICLE; CLINICAL RESEARCH; CLINICAL TRIAL; DEPRESSION; HAMILTON SCALE; HUMAN; LONGITUDINAL STUDY; NORMAL DISTRIBUTION; SENSITIVITY ANALYSIS; SIMULATION; STATISTICAL MODEL;

EID: 39849089597     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2007.00837.x     Document Type: Article

References (19)