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.
Using the logistic regression model, estimate the parameters that explain the variability of dichotomous or multinomial dependent variables. The estimated parameters are odds ratios.
Contingency tables, risk coefficients (relative risk, odds ratio), logistic regression, multinomial regression.
There are exercises for each of the topics covered.
Attending the TSC course or having knowledge of the topics it contains is preparatory.
It is advisable to attend the REG course.
The risk indices:
The logistic regression model:
The propensity score:
The different ways of application
The different types of matching
How to analyze matched data