Man pages for ygeunkim/propensityml
Propensity score weighting using machine learning methods
| add_propensity | Add estimated propensity score to a data frame |
| add_weighting | Treatment Effect Estimation Using Propensity Scores |
| build_covariate | Build covariance matrix of the covariates |
| chemical | Cohort Study Data about POISOX |
| compute_asam | Average Standardized Absolute Mean Distance |
| compute_balance | Covariate Balance |
| compute_ipw | Estimation of Inverse Probability Weighting |
| compute_sipw | Estimation of Stabilized Inverse Probability Weighting |
| estimate_ps | Estimation of Propensity Score |
| mc_setoguchi | Simulation Setting |
| outcome_frame | Potential Outcome Framework Toy Dataset |
| pipe | Pipe operator |
| plot_cp | Plot a Complexity Parameter Table |
| propensityml-package | propensityml: Propensity score weighting using machine... |
| propmod-class | 'propmod' class |
| ps_cart | Fitting CART for Propensity Score |
| ps_glm | Fitting Logistic Regression for Propensity Score |
| ps_prune | Pruning CART |
| ps_rf | Fitting Random Forests for Propensity Score |
| ps_svm | Fitting SVM for Propensity Score |
| sim_covariate | Simulating covariates |
| sim_outcome | Simulating Dataset for Various Scenarios |
