Statistical Primer: Propensity Score Matching and Its Alternatives

Propensity scores methods have proven incredibly useful in the analysis of observational datasets, as they allow for control of confounding variables. Moreover, they offer several benefits over the more ubiquitous multivariable regression approaches. Propensity score matching is a familiar tool, however there are several other propensity score-based methods, such as weighting and stratification. Benedetto and colleagues explore these different approaches and illustrate the methodology using a real-world example.