Propensity Score Matching

What is propensity score matching? 

Propensity score matching (PSM) is a statistical technique used in observational studies to reduce bias when estimating the effect of a treatment or intervention. It involves matching individuals in the treatment group with individuals in the control group who have similar characteristics based on their propensity scores—the probability of receiving the treatment given their baseline covariates. The goal is to create a balanced comparison group, making it more likely that any differences observed in outcomes are due to the treatment itself, rather than confounding variables. 

Why is propensity score matching important? 

Propensity score matching (PSM) is a valuable tool in observational research that allows for the creation of comparable treatment and control groups, making it possible to draw more valid conclusions about the effects of interventions or treatments. By reducing selection bias and balancing covariates, PSM enhances the credibility of causal inferences, making it a critical methodology for healthcare research, clinical trials, and policy evaluations where randomization is not possible.