title: Recurrent event data analysis with intermittently observed time-varying covariates.
abstract: Although recurrent event data analysis is a rapidly evolving area of research, rigorous studies on estimation of the effects of intermittently observed time-varying covariates on the risk of recurrent events have been lacking. Existing methods for analyzing recurrent event data usually require that the covariate processes are observed throughout the entire follow-up period. However, covariates are often observed periodically rather than continuously. We propose a novel semiparametric estimator for the regression parameters in the popular proportional rate model. The proposed estimator is based on an estimated score function where we kernel smooth the mean covariate process. We show that the proposed semiparametric estimator is asymptotically unbiased, normally distributed, and derives the asymptotic variance. Simulation studies are conducted to compare the performance of the proposed estimator and the simple methods carrying forward the last covariates. The different methods are applied to an observational study designed to assess the effect of group A streptococcus on pharyngitis among school children in India. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Biostatistics, Indiana University Fairbanks School of Public Health, Indianapolis, 46202, IN, U.S.A.
authors.forename: Shanshan
authors.initials: S
authors.lastname: Li
authors.affiliation: Department of Biostatistics, Johns Hopkins University, Baltimore, 21205, MD, U.S.A.
authors.forename: Yifei
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Department of Biostatistics, Johns Hopkins University, Baltimore, 21205, MD, U.S.A.|Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, 21205, MD, U.S.A.
authors.forename: Chiung-Yu
authors.initials: CY
authors.lastname: Huang
authors.affiliation: National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, 20817, MD, U.S.A.
authors.forename: Dean A
authors.initials: DA
authors.lastname: Follmann
authors.affiliation: National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, 20817, MD, U.S.A.
authors.forename: Richard
authors.initials: R
authors.lastname: Krause
mesh_terms: D002648:Child; D003198:Computer Simulation; D006801:Humans; D007194:India; D015233:Models, Statistical; D010612:Pharyngitis; D012008:Recurrence; D013223:Statistics as Topic; D013290:Streptococcal Infections
keywords: estimating equations; kernel smoothing; partial likelihood; recurrent events; survival analysis