Simple pattern-mixture models for longitudinal data with missing observations: analysis of urinary incontinence data.

@article{Park1999SimplePM,
  title={Simple pattern-mixture models for longitudinal data with missing observations: analysis of urinary incontinence data.},
  author={Taesung Park and Sun-Ho Lee},
  journal={Statistics in medicine},
  year={1999},
  volume={18 21},
  pages={2933-41}
}
In longitudinal studies each subject is observed at several different times. Longitudinal studies are rarely balanced and complete due to occurrence of missing data. Little proposed pattern-mixture models for the analysis of incomplete multivariate normal data. Later, Little proposed an approach to modelling the drop-out mechanism based on the pattern-mixture models. We advocate the pattern-mixture models for analysing the longitudinal data with binary or Poisson responses in which the… CONTINUE READING