Propensity Score

​

The Propensity Score matching technique is used to make observational data "similar" to randomized data. It is useful for numerous cases and with numerous explanatory variables.

​

​Objectives:

Using the logistic regression model, estimate the parameters that explain the variability of dichotomous or multinomial dependent variables. The estimated parameters are odds ratios.

 

Techniques presented:

Contingency tables, risk coefficients (relative risk, odds ratio), logistic regression, multinomial regression.

​

Tutorials:

There are exercises for each of the topics covered.

 

Prerequisites:

Attending the TSC course or having knowledge of the topics it contains is preparatory.

It is advisable to attend the REG course.

 

Subjects:

Contingency tables

The risk indices:

• Relative risk

• odds ratio

• Hazard Ratio

The logistic regression model:

• Binomial

• Multinomial

The propensity score:

• Its purposes

• The different ways of  application

• The different types of matching

• How to analyze matched data