Reasonably conduct the multiple Logistic regression analysis combined with the average treatment effect analysis

Abstract

The purpose of the paper was to introduce how to reasonably carry out multiple Logistic regression analysis combined with the average treatment effect analysis. Firstly， it introduced 4 basic concepts related to the average treatment effect analysis. Secondly， it presented the core contents in the average treatment effect analysis， that was， six estimation methods. Thirdly， through a hypothetical drug clinical trial example， it gave the whole process of how to use SAS software for the analysis. The contests were as follows： ① the traditional multiple Logistic regression model was used for the analysis； ② the propensity score model was used to calculate the inverse probability weights； ③ six estimation methods were used to estimate the potential outcome mean and the average treatment effect.

Keywords

• inverse probability weight
• potential outcome mean
• average treatment effect
• logistic regression model
• propensity score model