Regression Analysis of Additive Hazards Model With Latent Variables

Deng Pan, Haijin He, Xinyuan Song and Liuquan Sun

Journal of the American Statistical Association, 2015, vol. 110, issue 511, 1148-1159

Abstract: We propose an additive hazards model with latent variables to investigate the observed and latent risk factors of the failure time of interest. Each latent risk factor is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a hybrid procedure that combines the expectation-maximization (EM) algorithm and the borrow-strength estimation approach to estimate the model parameters. We establish the consistency and asymptotic normality of the parameter estimators. Various nice features, including finite sample performance of the proposed methodology, are demonstrated by simulation studies. Our model is applied to a study concerning the risk factors of chronic kidney disease for Type 2 diabetic patients. Supplementary materials for this article are available online.

Date: 2015
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Citations: View citations in EconPapers (9)

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DOI: 10.1080/01621459.2014.950083

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