Proportional Rate Model with Incomplete Covariate and Complete Auxiliary Information

This paper deals with the analysis of proportional rate model for recurrent event data when covariates are subject to missing. The true covariate is measured only on a randomly chosen validation set, whereas auxiliary information is available for all cohort subjects. To further utilize the auxiliary...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2015-12, Vol.44 (24), p.5285-5305
Main Authors: Xu, Zhibin, Liu, Luqin, Liu, Yanyan
Format: Article
Language:English
Subjects:
Asymptotic properties
Auxiliary covariate
Computer simulation
Econometrics
Estimating equation
Estimators
Mathematical analysis
Mathematical models
Monte Carlo simulation
Primary 62N02
Secondary 62G20
Proportional rate model
Recurrent event data
Regression
Samples
Statistics
Validation set
Citations: Items that this one cites
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Summary:This paper deals with the analysis of proportional rate model for recurrent event data when covariates are subject to missing. The true covariate is measured only on a randomly chosen validation set, whereas auxiliary information is available for all cohort subjects. To further utilize the auxiliary information to improve study efficiency, we propose an estimated estimating equation for the regression parameters. The resulting estimators are shown to be consistent and asymptotically normal. Both graphical and numerical techniques for checking the adequacy of the model are presented. Simulations are conducted to evaluate the finite sample performance of the proposed estimators. Illustration with a real medical study is provided.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2013.815776