Cutpoint determination methods in competing risks subdistribution model

Noor Akma Ibrahim, and Abdul Kudus, and Isa Daud, and Mohd. Rizam Abu Bakar, (2009) Cutpoint determination methods in competing risks subdistribution model. Journal of Quality Measurement and Analysis, 5 (1). pp. 103-117. ISSN 1823-5670

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In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. Five cutpoint determination methods are developed based on regression of competing risks subdistribution. Simulation results show that the deviance method has the desired properties. Permutation test is used to assess the level of significance and bootstrap confidence interval is obtained for the optimal cutpoint. The deviance method is applied to determine cutpoint of age for a real dataset

Item Type:Article
Keywords:cutpoint; competing risks; binary partitioning; regression analysis; 2-sample statistic; subdistribution function
Journal:Journal of Quality Measurement and Analysis
ID Code:1926
Deposited By: Ms. Nor Ilya Othman
Deposited On:20 Jun 2011 03:32
Last Modified:20 Jun 2011 03:32

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