Journal
JOURNAL OF BIOPHARMACEUTICAL STATISTICS
Volume 28, Issue 3, Pages 518-533Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10543406.2017.1333999
Keywords
Mixed poisson process; negative binomial process; overdispersion; pattern mixture models; rejection sampling
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Five algorithms are described for imputing partially observed recurrent events modeled by a negative binomial process, or more generally by a mixed Poisson process when the mean function for the recurrent events is continuous over time. We also discuss how to perform the imputation when the mean function of the event process has jump discontinuities. The validity of these algorithms is assessed by simulations. These imputation algorithms are potentially very useful in the implementation of pattern mixture models, which have been popularly used as sensitivity analysis under the non-ignorability assumption in clinical trials. A chronic granulomatous disease trial is analyzed for illustrative purposes.
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