Overview of logistic regression model analysis and application
10.3760/cma.j.issn.0253-9624.2019.09.018
- VernacularTitle: logistic族回归及其应用
- Author:
Qiqi WANG
1
;
Shicheng YU
;
Xiao QI
;
Yuehua HU
;
Wenjing ZHENG
;
Jiaxin SHI
;
Hongyan YAO
Author Information
1. Office of Epidemiology, Chinese Center for Disease Control and Prevention, Beijing 102206, China
- Publication Type:Journal Article
- Keywords:
Logistic models;
Odds ratio;
Evaluation studies
- From:
Chinese Journal of Preventive Medicine
2019;53(9):955-960
- CountryChina
- Language:Chinese
-
Abstract:
Logistic regression is a kind of multiple regression method to analyze the relationship between a binary outcome or categorical outcome and multiple influencing factors, including multiple logistic regression, conditional logistic regression, polytomous logistic regression, ordinal logistic regression and adjacent categorical logistic regression. This paper illustrates the basic principle, independent variable selection and assignment, applied condition, model evaluation and diagnosis for multiple logistic regression model. Moreover, the principle and application for polytomous logistic regression and ordinal logistic regression models were also introduced. By providing SAS codes and detailed explanations of the result for an example of obesity, readers could be able to better understand logistic regression model, and apply this method correctly to their research and daily work, so as to improve their capacity of the data analysis.
