Logistic回归模型及其应用

为了利用Logistic模型提高多分类定性因变量的预测准确率,在二分类Logistic回归模型的基础上,对实际统计数据建立三类别的Logistic模型.采用似然比检验法对自变量的显著性进行检验,剔除了不显著的变量;对每个类别的因变量都确定了1个线性回归函数,并进行了模型检验.分析结果表明,在处理因变量为定性变量的回归分析中,Logistic模型具有很好的预测准确度和实用推广性.

Logistic regression model and its application

To improve the forecasting accuracy of the multinomial qualitative dependent variable by using logistic model,ternary logistic model is established for actual statistical data based on binary logistic regression model.The significance of independent variables is tested by using the likelihood ratio test method to remove the non-significant variable.A linear regression function is determined for each category dependent variable,and the models are tested.The analysis results show that logistic regression model has good predictive accuracy and practical promotional value in handling regression analysis of qualitative dependent variable.