Cutpoint selection for discretizing a continuous covariate for generalized estimating equations

Author(s)

Tunes-da-Silva, Gisela ^[1] ; Klein, John P. ^[2]

Affiliation

^[1] Univ Sao Paulo, Dept Stat, Sao Paulo - Brazil

^[2] Med Coll Wisconsin, Dept Populat Hlth, Milwaukee, WI 53226 - USA

• Document type: Journal article
• Source: COMPUTATIONAL STATISTICS & DATA ANALYSIS; v. 55, n. 1, p. 226-235, JAN 1 2011.
• Web of Science Citations: 8

Abstract

We consider consider the problem of dichotomizing a continuous covariate when performing a regression analysis based on a generalized estimation approach. The problem involves estimation of the cutpoint for the covariate and testing the hypothesis that the binary covariate constructed from the continuous covariate has a significant impact on the outcome. Due to the multiple testing used to find the optimal cutpoint, we need to make an adjustment to the usual significance test to preserve the type-I error rates. We illustrate the techniques on one data set of patients given unrelated hematopoietic stem cell transplantation. Here the question is whether the CD34 cell dose given to patient affects the outcome of the transplant and what is the smallest cell dose which is needed for good outcomes. (C) 2010 Elsevier BM. All rights reserved. (AU)

• FAPESP's process: 07/02823-3 - Survival models for analysis of complex disease processes
• Grantee: Gisela Tunes da Silva
• Support Opportunities: Scholarships abroad - New Frontiers