主成分改进的Logistic回归模型方法在流行病学分析中的应用
改进,,多重共线性；Logistic回归；主成分分析,1原理与方法,2应用分析,3讨论,参考文献：
摘要：目的 探讨在涉及多自变量的Logistic回归分析中变量间多重共线性的诊断和处理方法。 方法 应用主成分改进的Logistic回归方法进行多重共线性变量的诊断与处理。 结果 去除了回归模型中变量间的多重共线性影响，建立了较为理想的关系模型。 结论 在Logistic回归模型分析中应用上述方法进行多重共线性的诊断和处理是有效及可行的。关键词：多重共线性；Logistic回归；主成分分析
中图分类号：R18125 文献标识码：A 文章编号：1009-9727(2005)02-207-03
Application of modified logistic regression model in the analysis of epidemiology QIU Jiong-liang1, ZHENG Jian-ning1, ZHANG Yang2 (Department of Health and Quarantine in Ningbo Entry-exit Inspection and Quarantine Bureau, Ningbo 315012, Zhejiang, PR China)
Abstract: Objective To explore the diagnosis and treatment of multivariable multicollinearity in the logistic regression analysis Methods The data with multivariable multicollinearity were diagnosed and treated using the logistic regression model method improved by principal component analysis Results The effect of multicollinearity among variables were eliminated in the regression model and an ideal mathematical model was constructed Conclusion The new method is effective and feasible for diagnosis and treatment of multivariable multicollinearity in the logistic regression model analysis ......
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