Table of Contents
International Journal of Quality, Statistics, and Reliability
Volume 2008, Article ID 471607, 10 pages
Research Article

Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model

School of Mathematical Sciences, University Sains Malaysia, 11800 Penang, Malaysia

Received 1 August 2008; Revised 17 October 2008; Accepted 25 November 2008

Academic Editor: Myong K. (MK) Jeong

Copyright © 2008 Jassim N. Hussain. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially if the models are complex and have a large number of risk factors. In this paper, we propose a new method based on the global sensitivity analysis (GSA) to select the most influential risk factors. This contributes to simplification of the logistic regression model by excluding the irrelevant risk factors, thus eliminating the need to fit and evaluate a large number of models. Data from medical trials are suggested as a way to test the efficiency and capability of this method and as a way to simplify the model. This leads to construction of an appropriate model. The proposed method ranks the risk factors according to their importance.