Estimation of cumalative rate function under informative truncation
Date Issued
2004
Date
2004
Author(s)
Huang, Chou-Yang
DOI
zh-TW
Abstract
Recurrent events data are usually encountered in longitudinal studies, like the re-hospitalization of the patient and the re-happening of the traffic accidents. In collecting recurrent events data, one of the popular way is that we don’t have to wait the recurrence of the first event in a short period of time but collect the sample who had their specific event after the beginning of the study. Data collected in this way is called the truncated data. Although it can shorten the time used in data collection , but it’s a biased data because the sample who had their specific event before the beginning of the study will be truncated. Non-informative truncation is usually assumed in analyzing truncated data, but it’s unrealistic in many situations. In this article, we will estimate the cumulative rate function under informative truncation.
At last, we will use simulation to find out the difference in estimating the cumulative rate function under informative truncation by our method and the naive method.
Subjects
左截切
累積發生率
left truncation
cumulative rate function
SDGs
Type
thesis
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