Introduction of reduced rank regression and development of a user-written Stata package.
10.3760/cma.j.cn112338-20210222-00136
- VernacularTitle:降秩回归方法简介及其Stata程序开发
- Author:
Bang ZHENG
1
;
Qi LIU
2
;
Jun LYU
2
;
Can Qing YU
2
Author Information
1. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China School of Public Health, Imperial College London, London W6 8RP, UK.
2. Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China.
- Publication Type:Journal Article
- MeSH:
China;
Humans;
Models, Statistical;
Public Health;
Regression Analysis
- From:
Chinese Journal of Epidemiology
2022;43(3):403-408
- CountryChina
- Language:Chinese
-
Abstract:
Reduced rank regression is an extended multivariate linear regression model with the function of dimension reduction. It has been more and more widely used in nutritional epidemiology research to understand people's dietary patterns in recent years. However, there has been no existing Stata package or command to implement reduced rank regression independently. Therefore, we developed a new user-written package named "rrr" for its implementation in Stata. This paper summarizes the methodology of reduced rank regression, the development and functions of the Stata rrr package and its application in the China Kadoorie Biobank dataset, with the aim of facilitating the future wide use of this statistical method in epidemiology and public health research.
