Statistical Analysis of Questionnaire Data via Cumulative Logistic Regression Model

Abstract

Based on a real questionnaire data, we build a cumulative logistic model to deal with the mutual relationship of the variables in the data. Aiming at the problem of too much designed variables, we apply statistical method to select those important ones and delete the useless ones without losing too much information. We also provide the analysis results for the data by the software SAS, and give some suggestions for the design of questionnaire. Our analysis also shows that the model built in paper can fit the questionnaire data very well, and it has higher preciseness rate of forecasting.