Propensity Scores

Propensity scores are a statistical technique used in observational studies to reduce bias by balancing the distribution of covariates between treatment and control groups. Propensity scores are the predicted probabilities of receiving a treatment based on observed covariates. These scores can be used to match individuals in the treatment and control groups or to stratify the sample into groups with similar propensity scores. Once the groups are balanced, the effect of the treatment can be estimated more accurately. Propensity scores can be estimated using various methods, including logistic regression, machine learning algorithms, and propensity score matching.
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