A Hot-Deck Multiple Imputation Procedure for Gaps in Longitudinal Recurrent Event Histories
Article first published online: 1 MAR 2011
© 2011, The International Biometric Society
Volume 67, Issue 4, pages 1573–1582, December 2011
How to Cite
Wang, C.-N., Little, R., Nan, B. and Harlow, S. D. (2011), A Hot-Deck Multiple Imputation Procedure for Gaps in Longitudinal Recurrent Event Histories. Biometrics, 67: 1573–1582. doi: 10.1111/j.1541-0420.2011.01558.x
- Issue published online: 14 DEC 2011
- Article first published online: 1 MAR 2011
- Received June 2010. Revised November 2010. Accepted November 2010.
- Hormone treatment;
- Menstrual periods;
- Missing data;
- Predictive mean matching;
- Terminal event
Summary We propose a regression-based hot-deck multiple imputation method for gaps of missing data in longitudinal studies, where subjects experience a recurrent event process and a terminal event. Examples are repeated asthma episodes and death, or menstrual periods and menopause, as in our motivating application. Research interest concerns the onset time of a marker event, defined by the recurrent event process, or the duration from this marker event to the final event. Gaps in the recorded event history make it difficult to determine the onset time of the marker event, and hence, the duration from onset to the final event. Simple approaches such as jumping gap times or dropping cases with gaps have obvious limitations. We propose a procedure for imputing information in the gaps by substituting information in the gap from a matched individual with a completely recorded history in the corresponding interval. Predictive mean matching is used to incorporate information on longitudinal characteristics of the repeated process and the final event time. Multiple imputation is used to propagate imputation uncertainty. The procedure is applied to an important data set for assessing the timing and duration of the menopausal transition. The performance of the proposed method is assessed by a simulation study.