| Liu Yuanyuan,Li Changping,Hu Liangping,One-level multiple Logistic regression analysis of the multi-value nominal data collected from the complex sampling survey design[J].SICHUAN MENTAL HEALTH,2019,32(6):490-494 |
| One-level multiple Logistic regression analysis of the multi-value nominal data collected from the complex sampling survey design |
DOI：10.11886/scjsws20191119005 |
| English keywords:Complex sampling Multi-value nominal data Logistic regression analysis Sampling weights |
| Fund projects:国家高技术研究发展计划课题资助 2015AA020102;国家自然科学基金项目 81803333国家高技术研究发展计划课题资助（2015AA020102）；国家自然科学基金项目（81803333） |
| Author Name | Affiliation | | Liu Yuanyuan | 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 article was to introduce the construction of multiple logistic regression models with multi-value nominal data collected from the complex sampling survey design, and to explore the differences between different strategies. Using the LOGISTIC procedure and the SURVEYLOGISTIC procedure in SAS software, generalized logistics regression models were constructed based on whether the sampling design or the sampling weights were considered, and the results were compared.The results obtained by different analysis strategies showed that not only the values of parameter estimation, the standard error of the regression coefficients, the OR value and its confidence intervals were different, but also the explanatory variables in the established models were also different. When constructing a generalized logistics regression model for multi-value nominal data of complex sampling design, both the sampling design and the sampling weights should be considered. Otherwise, even if the sample size was large enough, it would lead to the erroneous inference conclusions. |
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