Propensity matching is a statistical technique used in observational studies to reduce bias and mimic the randomization process of a controlled experiment. This method aims to create a comparable or matched group of subjects who have similar characteristics but differ in the treatment or exposure variable of interest. The goal is to control for potential confounding variables and make the treatment and control groups more similar on observed characteristics, thus improving the validity of causal inferences.

The process involves identifying a set of covariates (variables that may influence both the treatment assignment and the outcome) and then matching treated and untreated subjects based on these covariates. This helps ensure that any differences in outcomes between the two groups can be more confidently attributed to the treatment rather than confounding factors.

Propensity matching is commonly used in observational studies when random assignment to treatment groups is not feasible or ethical, and researchers want to minimize the impact of potential confounding variables.