Modeling repeated count data subject to informative dropout.

@article{Albert2000ModelingRC,
  title={Modeling repeated count data subject to informative dropout.},
  author={Paul S. Albert and Dean A Follmann},
  journal={Biometrics},
  year={2000},
  volume={56 3},
  pages={667-77}
}
In certain diseases, outcome is the number of morbid events over the course of follow-up. In epilepsy, e.g., daily seizure counts are often used to reflect disease severity. Follow-up of patients in clinical trials of such diseases is often subject to censoring due to patients dying or dropping out. If the sicker patients tend to be censored in such trials, estimates of the treatment effect that do not incorporate the censoring process may be misleading. We extend the shared random effects… CONTINUE READING

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