期刊
JOURNAL OF BIOPHARMACEUTICAL STATISTICS
卷 28, 期 3, 页码 518-533出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/10543406.2017.1333999
关键词
Mixed poisson process; negative binomial process; overdispersion; pattern mixture models; rejection sampling
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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