Basic Theory and Methodology
Introduction of reduced rank regression and development of a user-written Stata package
Zheng Bang, Liu Qi, Lyu Jun, Yu Canqing
Published 2022-03-10
Cite as Chin J Epidemiol, 2022, 43(3): 403-408. DOI: 10.3760/cma.j.cn112338-20210222-00136
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.
Key words:
Reduced rank regression; Epidemiology; Application; Software implementation
Contributor Information
Zheng Bang
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
Liu Qi
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
Lyu Jun
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
Yu Canqing
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
