Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15739
Title: A class of mixed models for recurrent event data
Authors: Sun, L
Zhao, X 
Zhou, J
Keywords: Counting process
Marginal rate model
Mixed model
Partial-score function
Proportional and Convergent effects
Issue Date: 2011
Publisher: Wiley-Blackwell
Source: Canadian journal of statistics, 2011, v. 39, no. 4, p. 578-590 How to cite?
Journal: Canadian Journal of Statistics 
Abstract: In this article, we propose a class of mixed models for recurrent event data. The new models include the proportional rates model and Box-Cox transformation rates models as special cases, and allow the effects of covariates on the rate functions of counting processes to be proportional or convergent. For inference on the model parameters, estimating equation approaches are developed. The asymptotic properties of the resulting estimators are established and the finite sample performance of the proposed procedure is evaluated through simulation studies. A real example with data taken from a clinic study on chronic granulomatous disease (CGD) is also illustrated for the use of the proposed methodology.
URI: http://hdl.handle.net/10397/15739
DOI: 10.1002/cjs.10132
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