Marginal means/rates models for multiple type recurrent event data.
Recurrent events are frequently observed in biomedical studies, and often more than one type of event is of interest. Follow-up time may be censored due to loss to follow-up or administrative censoring. We propose a class of semi-parametric marginal means/rates models, with a general relative risk form, for assessing the effect of covariates on the censored event processes of interest. We formulate estimating equations for the model parameters, and examine asymptotic properties of the parameter estimators. Finite sample properties of the regression coefficients are examined through simulations. The proposed methods are applied to a retrospective cohort study of risk factors for preschool asthma.
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7420, USA. cai@bios.unc.edu
Jianwen
J
Cai
Douglas E
DE
Schaubel
D001249:Asthma / Q000453:epidemiology / Q000473:pathology; D002170:Canada; D002675:Child, Preschool; D015331:Cohort Studies; D003198:Computer Simulation; D006760:Hospitalization; D006801:Humans; D007223:Infant; D016014:Linear Models; D015233:Models, Statistical; D009819:Office Visits; D012008:Recurrence; D012307:Risk Factors; D018709:Statistics, Nonparametric; D016019:Survival Analysis