The propensity score methods are widely used to adjust confounding effects in observational studies when comparing treatment effects. The propensity score is defined as the probability of treatment assignment conditioning on some observed baseline characteristics and it provides a balanced score for the treatment conditions as conditioning on the propensity score, the treatment groups are comparable in terms of the baseline covariates. In this chapter, we will first provide an overview of the propensity score and the underlying assumptions for using propensity score, we will then discuss four methods based on propensity score: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score, as well as the differences among the four methods.
