Introduction -- Counterfactual framework and assumptions -- Conventional methods for data balancing -- Sample selection and related models -- Propensity score matching and related models -- Propensity score subclassification -- Propensity score weighting -- Matching estimators -- Propensity score analysis with nonparametric regression -- Propensity score analysis of categorical or continuous treatments -- Selection bias and sensitivity analysis -- Concluding remar