Feng Siyuan,Li Changping,Hu Liangping,Multi-level multiple Logistic regression analysis of the multi-value ordinal data collected from the unpaired design[J].SICHUAN MENTAL HEALTH,2019,32(6):481-485

Multi-level multiple Logistic regression analysis of the multi-value ordinal data collected from the unpaired design

DOI：10.11886/scjsws20191119003

English keywords:Multi-value ordinal dependent variables Multi-level Cumulative logistic regression model SAS realization

Fund projects:国家高技术研究发展计划课题资助 2015AA020102 国家高技术研究发展计划课题资助（2015AA020102）

Author Name	Affiliation
Feng Siyuan	Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
Li Changping	Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China Specialty Committee of Clinical Scientific Research Statistics of World Federation of Chinese Medicine Societies, Beijing 100029, China
Hu Liangping	Specialty Committee of Clinical Scientific Research Statistics of World Federation of Chinese Medicine Societies, Beijing 100029, China Graduate School, Academy of Military Sciences PLA China, Beijing 100850, China

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English abstract:

The purpose of this study was to introduce the multi-level multiple logistic regression analysis of the multi-value ordinal data. This method was based on the hierarchical data to build a regression model with the multi-value ordinal dependent variables changing with a group of independent variables. The specific methods were as follows. First, introduced the basic concepts. Second, presented the data structure to be analyzed. Third, briefly introduced the construction and solution of the regression models. Fourth, introduced in detail of how to use the procedures of GLIMMIX and NLMIXED of SAS software to fit the regression model, and explained and compared the relevant results. Last, the problems that should be paid attention to in cumulative logistic regression model fitting under the multi-layer structure data were discussed.

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