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Cox's Model for Prison Partly Interval Censored Data
The term survival analysis has been used in examines and models the time until the events occur. The most common tool for studying the dependency of survival time on predictor variables is Cox model proportional hazards regression model. In this paper we present a simple modification of Cox's p...
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Published in: | Journal of physics. Conference series 2020-03, Vol.1489 (1), p.12032 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The term survival analysis has been used in examines and models the time until the events occur. The most common tool for studying the dependency of survival time on predictor variables is Cox model proportional hazards regression model. In this paper we present a simple modification of Cox's proportional hazards model using the partial likelihood principle technique based on Newton Rapson method. Simulation is conducted based on prison partly interval censored data set with particular sample sizes to evaluate the performance of the proposed model, and it shows that the model is feasible and works well. |
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ISSN: | 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/1489/1/012032 |