| Li Changping,Zhang Tiantian,Song Desheng,Hu Liangping,Multilevel multiple Logistic regression analysis with the multi-value nominal data collected from the unpaired design[J].SICHUAN MENTAL HEALTH,2019,32(6):495-500 |
| Multilevel multiple Logistic regression analysis with the multi-value nominal data collected from the unpaired design |
DOI：10.11886/scjsws20191119006 |
| English keywords:Multi-value nominal data Multilevel SAS software Multiple logistic regression analysis |
| 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 | | 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 | | Zhang Tiantian | Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China | | Song Desheng | Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin 300070, 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 the paper was to introduce the construction and solution of multilevel multiple logistic regression analysis with the multi-value nominal data collected from the unpaired design. Firstly, the basic concepts related to “multi-value nominal outcome variables” “stratified or multilevel data structures” and “generalized multiple logistic regression models” were introduced. Secondly, a cross-sectional survey data with two-level was presented. The data contained many independent variables and a multi-value ordinal outcome variable (in this paper, it was treated as a multi-value nominal outcome variable). Finally, statistical analysis of data was performed by two procedures (GLIMMIX and NLMIXED) in the SAS software. Construction and solution of multilevel multiple logistic regression analysis with the multi-value nominal data collected from the unpaired design was preformed and the related output results were compared and explained. |
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