What are the Steps Involved in Propensity Score Matching?
1. Model Specification: Choose the covariates that need to be balanced between the treated and untreated groups. 2. Estimation of Propensity Scores: Use a logistic regression model to estimate the propensity scores. 3. Matching: Match treated and untreated subjects based on their propensity scores using methods such as nearest-neighbor matching, caliper matching, or kernel matching. 4. Balance Checking: Assess the balance of covariates between the matched groups using statistical tests or standardized mean differences. 5. Outcome Analysis: Compare the outcomes between the matched groups to estimate the treatment effect.
