Selection models and pattern-mixture models for incomplete data with covariates.
Most models for incomplete data are formulated within the selection model framework. This paper studies similarities and differences of modeling incomplete data within both selection and pattern-mixture settings. The focus is on missing at random mechanisms and on categorical data. Point and interval estimation is discussed. A comparison of both approaches is done on side effects in a psychiatric study.
Michiels
B
B
Biostatistics, Limburgs Universitair Centrum, Diepenbeek, Belgium.
Molenberghs
G
G
Lipsitz
S R
SR
D001699:Biometry; D003627:Data Interpretation, Statistical; D005260:Female; D016666:Fluvoxamine / Q000009:adverse effects / Q000627:therapeutic use; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D001523:Mental Disorders / Q000188:drug therapy; D015233:Models, Statistical; D017367:Selective Serotonin Reuptake Inhibitors / Q000009:adverse effects / Q000627:therapeutic use
D016666:Fluvoxamine; D017367:Selective Serotonin Reuptake Inhibitors