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Analysis of stage IV rectal cancer with discrete times
Journal of the Korean Data & Information Science Society 2019;30:183-92
Published online January 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.1.183
© 2019 Korean Data and Information Science Society.

Minjung Lee1

1Division of Economics & Information Statistics, Kangwon National University
Correspondence to: Assistant professor, Division of Economics & Information Statistics, Kangwon National University, Chuncheon, 24341, Korea. E-mail: mlee@kangwon.ac.kr
Received November 4, 2018; Revised December 30, 2018; Accepted December 30, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In the analysis of survival data, most analysis methods have been developed based on continuous time data. However, discrete event times may be observed. It would be appropriate to use a discrete time model for analyses of such data. In this paper, we studied regression analyses of discrete time survival data. We used maximum likelihood inferences for estimation of the parameters in a discrete hazards model and presented prediction for the discrete survival function. We fitted the discrete time proportional odds model to stage IV rectal cancer data obtained from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute and estimated the survival probability for a patient with specific covariate values under the discrete time proportional odds model. We evaluated calibration and discriminatory accuracy of the fitted model using calibration plot and time-dependent area under the ROC curve. Through these results, we confirmed the validity of the fitted model.
Keywords : Discrete hazard function, discrete time model, discrete survival function, stage IV rectal cancer.