Man pages for jackcollison/causality
Tools for Performing Causal Inference with Observational Data
| aipw_ate | Estimate average treatment effect (ATE) with augmented... |
| aipw_rf_att | Estimate the average treatment effect on the treated (ATT)... |
| assess_covariate_balance | Assess balance in multivariate covariate distributions... |
| balance_plot | Assess balance in covariate distribution graphically. |
| check_propensity | Check calibration and overlap assumptions via plot. |
| double_selection_ate | Estimate average treatment effect (ATE) with double selection... |
| general_match | Performs general matching with exact and mahalanobis... |
| ipw_ate | Etimate average treatment effect (ATE) with inverse... |
| lalonde | Lalonde Data |
| naive_ate | Estimate naive average treatment effect (ATE). |
| propensity_match | Performs propensity score matching. |
| propensity_score | Calculate propensity scores. |
| propensity_strat_ate | Estimate average treatment effect (ATE) with propensity score... |
| prop_weighted_ols_ate | Estimate average treatment effect (ATE) with inverse... |
| rf_att | Uses random forests to naively estimate the average treatment... |
| s_learner | Estimate heterogeneous treatment effects (HTEs) using the... |
| t_learner | Estimate heterogeneous treatment effects (HTEs) using the... |
| univariate_balance_plot | Assess balance for a single covairate. |
| x_learner | Estimate heterogeneous treatment effects (HTEs) using the... |
