Analysis of Recurrent Event Data Under the Case-crossover Design with Applications to Elderly Falls

Xianghua Luo
Division of Biostatistics
University of Minnesota

Wednesday, November 28, 2007
3:30pm
MoosT 1-450G
Minneapolis Campus

Abstract:
The case-crossover design is useful for studying the effects of transient exposures on short-term risk of diseases or injuries when only data on cases are available. The crossover nature of this design allows each subject to serve as his own control. While the original design was proposed for univariate event data, in many applications recurrent events are often encountered (e.g., elderly falls, gout attacks, and sexually transmitted infections). In such situations, the within-subject dependence among recurrent events needs to be taken into account in the analysis. We review three existing conditional logistic regression-based approaches for analyzing recurrent event data under the case-crossover design. A simple approach is to use only one (e.g. the first) event for each subject, such that no assumption on the correlation among multiple events is needed, while we would expect loss of efficiency in estimation. The validity of the other two reviewed approaches rely on independence assumptions for the recurrent events, conditionally on a subject-level latent variable and a set of observed time-varying covariates. In this paper, we propose to adjust the conditional logistic regression using either a within-subject pairwise resampling technique or a weighted estimating equation. No specific dependency structure among the recurrent events is needed for these two methods. We also propose a weighted Mantel-Haenszel estimator for situations with a binary exposure. Simulation studies are conducted to evaluate the performance of the discussed methods. We present the analysis of a study of the effect of medication changes on falls among the elderly.

A social tea will be held at 3:00 P.M. in A434 Mayo. All are Welcome.
For more details contact 612-624-4655 or see http://www.biostat.umn.edu/seminar_academic.html