A hot-deck multiple imputation procedure for gaps in longitudinal data on recurrent events
A hot-deck multiple imputation procedure for gaps in longitudinal data on recurrent events
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DOI：
10.1002/sim.2939
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发表时间：
2008-01-15
影响因子：
2
通讯作者：
Harlow, Sioban D.
中科院分区：
文献类型：
--
作者：
Little, Roderick J.;Yosef, Matheos;Harlow, Sioban D.
我们考虑对包括重复事件的时间的纵向数据集的分析，其中感兴趣的是变量，这些变量是每个个体的事件数量和事件之间的时间间隔的函数，并且当信息没有被记录时，某些情况下存在间隙。丢弃有空白的案件会导致在这些案件中记录的信息丢失。其他策略，如简单地将差距前后的间隔拼接在一起，可能会导致偏见。开发了一种相对简单的归罪方法，该方法基于完全记录的历史匹配来确定差距内事件的数量和次数。多重推算被用来传播推算不确定性。该程序是为月经日历数据开发的，其中反复发生的事件是随着时间的推移纵向记录的月经出血。记录有些繁琐，导致日历数据中存在空白。该程序被应用于评估更年期转变的两个重要数据集，墨尔本妇女中年健康项目和TREMIN数据。给出了一个仿真研究来评估所提出的方法的统计特性。还考虑了该方法的一些可能的扩展。版权所有(C)2007 John Wiley&Sons，Ltd.
We consider the analysis of longitudinal data sets that include times of recurrent events, where interest lies in variables that are functions of the number of events and the time intervals between events for each individual, and where some cases have gaps when the information was not recorded. Discarding cases with gaps results in a loss of the recorded information in those cases. Other strategies such as simply splicing together the intervals before and after the gap potentially lead to bias. A relatively simple imputation approach is developed that bases the number and times of events within the gap on matches to completely recorded histories. Multiple imputation is used to propagate imputation uncertainty. The procedure is developed here for menstrual calendar data, where the recurrent events are menstrual bleeds recorded longitudinally over time. The recording is somewhat onerous, leading to gaps in the calendar data. The procedure is applied to two important data sets for assessing the menopausal transition, the Melbourne Women's Midlife Health Project and the TREMIN data. A simulation study is presented to assess the statistical properties of the proposed procedure. Some possible extensions of the approach are also considered. Copyright (c) 2007 John Wiley & Sons, Ltd.