Prediction Using Logistic Regression Analysis of Peripheral Vascular Disease

Logisic regression model is to study the response variable is an important analytical method for non-continuous variables. Linear regression models and quantitative analysis is one of the most commonly used data mining methods of statistical analysis, linear regression analysis but generally require the response is a continuous variable, the data distribution is normal conditions. This study used logistic regression analysis to predict the study of peripheral vascular disease in the carotid atherosclerosis disease prediction model was established to provide scientific basis for the clinical treatment of peripheral vascular disease.