Paper Info
Title
An alternative estimation method for the accelerated failure time frailty model
Abstract
Frailty models based on the proportional hazards model are useful to analyze correlated or clustered failure time data. However, there has been some recent interest in a frailty model based on the popular accelerated failure time model for correlated failure time data ([Pan, W., 2001. Using frailties in the accelerated failure time model. Lifetime Data Anal. 7(1), 55-64], for example). In this paper we review recent advances on this model in the literature. We propose a general estimation method based on M-estimators and the EM algorithm to estimate the parameters in the model. To evaluate the performance of the proposed method, we carry out a simulation study. The results of the simulation study show that the proposed method performs well in comparison with existing estimation methods. As an illustration, the model and the proposed method are applied to analyze the effects of sublingual nitroglycerin and oral isosorbide dinitrate on angina pectoris of coronary heart disease patients [Danahy, D.T., Burwell, D.T., Aronow, W.S., Prakash, R., 1977. Sustained hemodynamic and antianginal effect of high dose oral isosorbide dinitrate. Circulation 55, 381-387].
Year
DOI
Venue
2007
10.1016/j.csda.2006.06.017
Computational Statistics & Data Analysis
Keywords
Field
DocType
proportional hazards model,correlated failure time data,oral isosorbide dinitrate,accelerated failure time frailty,popular accelerated failure time,general estimation method,failure time data,frailty model,accelerated failure time model,alternative estimation method,estimation method,em algorithm,proportional hazard model,accelerated failure time
Econometrics,M-estimator,Time data,Accelerated failure time model,Proportional hazards model,Expectation–maximization algorithm,Statistical simulation,Angina,Statistics,Mathematics,Isosorbide dinitrate
Journal
Volume
Issue
ISSN
51
9
Computational Statistics and Data Analysis
Citations 
PageRank 
References 
2
0.58
0
Authors
2
Name
Order
Citations
PageRank
Jiajia Zhang12616.64
Yingwei Peng23814.54