文献类型：期刊文献

中文题名：Logistic回归的主成分改进方法探讨及其医学应用

英文题名：The Study on the Enhancing Methods of Principal Component of Logistic Regression and Their Application to Medicine

作者：周菲[1];焦桂梅[1];赵凤兰[1];魏兴民[1]

第一作者：周菲

机构：[1]甘肃中医学院公共课部,兰州730000

第一机构：甘肃中医药大学

年份：2014

卷号：27

期号：1

起止页码：25

中文期刊名：数理医药学杂志

外文期刊名：Journal of Mathematical Medicine

基金：甘肃省教育科学"十二五"规划课题([2012]GSGXG037)

语种：中文

中文关键词：Logistic回归;多重共线性;主成分回归;SPSS17;0

外文关键词：Logistic regression;multi-collinearity; principal component regression~ SPSS17.0

摘要：研究Logistic回归模型的主成分回归改进方法。在医学研究中,尤其是在流行病的发病因素分析中,应用主成分回归进行多重共线性的改进处理,可以削减自变量观察矩阵之间的多重共线性,建立较为理想的关系模型,提高结果的可靠性;便于医学研究者正确合理的建立Logistic回归模型,处理混杂因素,预测疾病和判别分类。
This article mainly studies the enhancing methods of the principal component of Logistic Re- gression. In medical research, especially in the analyses of the aetiological agents of opidemics, the applica- tion of principal component regression to the improvements o{ multi-eollinearity can reduce the multi-col- linearity between matrices of variables , build up relatively ideal relation models and improve the reliability of results. Meanwhile, it enables medical researchers to establish rational Logistic Regression models, deal with thorny problems, predict diseases and elassify them.