An overview of multiple linear regression model and its application
10.3760/cma.j.issn.0253-9624.2019.06.021
- VernacularTitle: 多重线性回归模型及其应用
- Author:
Yuehua HU
1
;
Shicheng YU
;
Xiao QI
;
Wenjing ZHENG
;
Qiqi WANG
;
Hongyan YAO
Author Information
1. Office of Epidemiology, Chinese Center for Disease Control and Prevention, Beijing 102206, China
- Publication Type:Journal Article
- Keywords:
Linear models;
Regression analysis;
Models, statistical
- From:
Chinese Journal of Preventive Medicine
2019;53(6):653-656
- CountryChina
- Language:Chinese
-
Abstract:
Multiple Linear Regression (MLR) is a generalization of simple linear regression and is one of the commonly used models in multivariate statistical analysis. This article introduces the MLR model from the perspective of practical application. Four parts, including basic principle, application examples, the application condition and diagnosis, and the extension of the model, are sequentially illustrated in this article. Particularly, in the last part, alternative methods of the model are introduced when the application condition of the model is not met. We sincerely hope that this article could make our audiences have a better understanding of the MLR model in order to improve the efficiency of data utilization and statistical analysis by correctly performing this model in their research.
