TY - JOUR
T1 - Semiparametric additive marginal regression models for multiple type recurrent events
AU - Chen, Xiaolin
AU - Wang, Qihua
AU - Cai, Jianwen
AU - Shankar, Viswanathan
PY - 2012/10
Y1 - 2012/10
N2 - Recurrent event data are often encountered in biomedical research, for example, recurrent infections or recurrent hospitalizations for patients after renal transplant. In many studies, there are more than one type of events of interest. Cai and Schaube (Lifetime Data Anal 10:121-138, 2004) advocated a proportional marginal rate model for multiple type recurrent event data. In this paper, we propose a general additive marginal rate regression model. Estimating equations approach is used to obtain the estimators of regression coefficients and baseline rate function. We prove the consistency and asymptotic normality of the proposed estimators. The finite sample properties of our estimators are demonstrated by simulations. The proposed methods are applied to the India renal transplant study to examine risk factors for bacterial, fungal and viral infections.
AB - Recurrent event data are often encountered in biomedical research, for example, recurrent infections or recurrent hospitalizations for patients after renal transplant. In many studies, there are more than one type of events of interest. Cai and Schaube (Lifetime Data Anal 10:121-138, 2004) advocated a proportional marginal rate model for multiple type recurrent event data. In this paper, we propose a general additive marginal rate regression model. Estimating equations approach is used to obtain the estimators of regression coefficients and baseline rate function. We prove the consistency and asymptotic normality of the proposed estimators. The finite sample properties of our estimators are demonstrated by simulations. The proposed methods are applied to the India renal transplant study to examine risk factors for bacterial, fungal and viral infections.
KW - Additive model
KW - Empirical process
KW - Multiple type recurrent events
KW - Recurrent events
UR - http://www.scopus.com/inward/record.url?scp=84866377556&partnerID=8YFLogxK
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U2 - 10.1007/s10985-012-9226-4
DO - 10.1007/s10985-012-9226-4
M3 - Article
C2 - 22899088
AN - SCOPUS:84866377556
SN - 1380-7870
VL - 18
SP - 504
EP - 527
JO - Lifetime Data Analysis
JF - Lifetime Data Analysis
IS - 4
ER -