郑棒,刘琪,吕筠,余灿清.降秩回归方法简介及其Stata程序开发[J].Chinese journal of Epidemiology,2022,43(3):403-408 |
降秩回归方法简介及其Stata程序开发 |
Introduction of reduced rank regression and development of a user-written Stata package |
Received:February 22, 2021 |
DOI:10.3760/cma.j.cn112338-20210222-00136 |
KeyWord: 降秩回归 流行病学 应用 软件实现 |
English Key Word: Reduced rank regression Epidemiology Application Software implementation |
FundProject:国家自然科学基金(81973125) |
Author Name | Affiliation | E-mail | 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 | yucanqing@pku.edu.cn |
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Abstract: |
降秩回归是一种用于降维的多变量线性回归,近年来被越来越多的应用于营养流行病学领域来提取膳食模式。但Stata软件作为主流的统计分析工具之一,目前尚无进行降秩回归的程序。本文介绍了降秩回归方法的基本思想、实现降秩回归的基本原理,并开发和公开发布了功能全面的Stata程序(rrr),最后结合中国慢性病前瞻性研究数据进行示例分析。rrr程序的研发和公开,为该统计方法在流行病学和公共卫生领域的广泛应用提供了实用工具。 |
English 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. |
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