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Estimation of conditional mean residual life function with random censored data  

Lee, Won-Kee (School of Medicine, Kyungpook National University)
Song, Myung-Unn (Department of Statistics, Kyungpook National University)
Jeong, Seong-Hwa (Faculty of Health Science, Daegu Haany University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.1, 2011 , pp. 89-97 More about this Journal
Abstract
The aims of this study were to propose a method of estimation for mean residual life function (MRLF) from conditional survival function using the Buckley and James's (1979) pseudo random variables, and then to assess the performance of the proposed method through the simulation studies. The mean squared error (MSE) of proposed method were less than those of the Cox's proportional hazard model (PHM) and Beran's nonparametric method for non-PHM case. Futhermore in the case of PHM, the MSE's of proposed method were similar to those of Cox's PHM. Finally, to evaluate the appropriateness of practical use, we applied the proposed method to the gastric cancer data. The data set consist of the 1, 192 patients with gastric cancer underwent surgery at the Department of Surgery, K-University Hospital.
Keywords
Conditional mean residual life function; conditional survival function; random censoring;
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Times Cited By KSCI : 2  (Citation Analysis)
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