| Gong Xiaowen,Li Changping,Hu Liangping,One-level multiple Logistic regression analysis of the nominal data collected from the unpaired design[J].SICHUAN MENTAL HEALTH,2019,32(6):486-489 |
| One-level multiple Logistic regression analysis of the nominal data collected from the unpaired design |
DOI：10.11886/scjsws20191119004 |
| English keywords:Multi-value nominal data Logistic regression analysis Variables selection Design matrix |
| 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 | | Gong Xiaowen | 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 paper introduced the basic principle, modeling strategy and key points of the one-level multiple logistic regression analysis of the multi-value nominal data collected from the unpaired design. In order to analyze the influencing factors of the choice of treatment for patients with non-ST-segment elevation myocardial infarction(NSTEMI) of the real example, and to predict the appropriate treatment according to the important characteristics, it was built that the one-level multiple nominal logistic regression model with and without variable selection by using SAS 9.4 software. The regression results showed that the regression coefficients of the same variable had algebraic relations in different logit functions. Multiple nominal logistic regression analysis could deal with the regression problem of the multi-value nominal data and with the help of SAS software. We could establish a concise model by filtering the insignificant independent variables. |
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