Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model
Author
Source
International Journal of Quality, Statistics, and Reliability
Issue
Vol. 2008, Issue 2008 (31 Dec. 2008), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-02-05
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Economics & Business Administration
Economy
Abstract EN
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.
American Psychological Association (APA)
Hussain, Jassim N.. 2009. Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model. International Journal of Quality, Statistics, and Reliability،Vol. 2008, no. 2008, pp.1-10.
https://search.emarefa.net/detail/BIM-474148
Modern Language Association (MLA)
Hussain, Jassim N.. Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model. International Journal of Quality, Statistics, and Reliability No. 2008 (2008), pp.1-10.
https://search.emarefa.net/detail/BIM-474148
American Medical Association (AMA)
Hussain, Jassim N.. Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model. International Journal of Quality, Statistics, and Reliability. 2009. Vol. 2008, no. 2008, pp.1-10.
https://search.emarefa.net/detail/BIM-474148
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-474148