| 非配对设计多值有序资料一水平多重Logistic回归分析 |
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| 引用本文： | 凤思苑,李长平,胡良平.非配对设计多值有序资料一水平多重Logistic回归分析[J].四川精神卫生,2019,32(5):395-399. |
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| 作者姓名： | 凤思苑 李长平 胡良平 |
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| 作者单位： | 天津医科大学公共卫生学院卫生统计学教研室,天津医科大学公共卫生学院卫生统计学教研室；世界中医药学会联合会临床科研统计学专业委员会,世界中医药学会联合会临床科研统计学专业委员会；军事科学院研究生院 |
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| 基金项目： | 国家高技术研究发展计划课题资助（2015AA020102） |
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| 摘 要： | 本文目的是介绍非配对设计多值有序资料一水平多重logistic回归模型的构建与求解方法。本文详细介绍了构建累积logistic回归模型的原理和具体方法,并结合实例介绍如何使用SAS软件中的LOGISTIC过程来拟合此回归模型,并对逐步回归法的输出结果进行了解释;其次讨论了有关构建累积logistic回归模型的过程中自变量筛选、模型评价以及拟合模型时需注意的问题。
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| 关 键 词： | 多值有序因变量 累积logistic回归分析 自变量筛选 模型评价 SAS实现 |
| 收稿时间： | 2019/9/27 0:00:00 |
One-level multiple Logistic regression analysis with the multi-value ordered data collected from the unpaired design |
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| Feng Siyuan,Li Changping and Hu Liangping.One-level multiple Logistic regression analysis with the multi-value ordered data collected from the unpaired design[J].Sichuan Mental Health,2019,32(5):395-399. |
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| Authors: | Feng Siyuan Li Changping and Hu Liangping |
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| Institution: | Department of Health Statistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China,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 and 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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| Abstract: | The purpose of this paper was to introduce the construction and solution of one-level multiple logistic regression models for unpaired design multi-value ordered data. This paper introduced the principle and methods of cumulative logistic regression model in detail, and introduced how to use the LOGISTIC procedure of SAS software to fit the regression model, and explained the results of the screening independent variables by using stepwise method. In addition, the paper discussed the problems that should be paid attention to in the process of constructing the cumulative logistic regression model, such as independent variable selection, model evaluation and model fitting. |
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| Keywords: | Multi-value ordered dependent variables Cumulative logistic regression analysis Independent variable selection Model evaluation SAS realization |
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