Statistical Analysis of Bivariate Recurrent Event Data with Incomplete Observation Gaps
자연과학 > 통계학
( Yang Jin Kim )
CSAM(Communications for Statistical Applications and Methods) 2013년, 제20권 제4호, 283~290페이지(총8페이지)
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    Subjects can experience two types of recurrent events in a longitudinal study. In addition, there may exist intermittent dropouts that results in repeated observation gaps during which no recurrent events are observed. Therefore, theses periods are regarded as non-risk status. In this paper, we consider a special case where information on the observation gap is incomplete, that is, the termination time of observation gap is not available while the starting time is known. For a statistical inference, incomplete termination time is incorporated in terms of interval-censored data and estimated with two approaches. A shared frailty effect is also employed for the association between two recurrent events. An EM algorithm is applied to recover unknown termination times as well as frailty effect. We apply the suggested method to young drivers` convictions data with several suspensions.
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