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 f...

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Bibliographic Details
Published in:Lifetime data analysis 2004-06, Vol.10 (2), p.121-138
Main Authors: Cai, Jianwen, Schaubel, Douglas E
Format: Article
Language:English
Subjects:
Asthma
Asthma - epidemiology
Asthma - pathology
Biostatistics
Canada
Child, Preschool
Cohort analysis
Cohort Studies
Computer Simulation
Hospitalization
Humans
Infant
Infections
Linear Models
Mathematical models
Models, Statistical
Office Visits
Recurrence
Risk Factors
Simulation
Skin cancer
Statistical analysis
Statistics, Nonparametric
Studies
Survival Analysis
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Summary: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.
ISSN:1380-7870
1572-9249
DOI:10.1023/B:LIDA.0000030199.23383.45