Function reference • personalized

Main Functions
`fit.subgroup()`	Fitting subgroup identification models
`validate.subgroup()`	Validating fitted subgroup identification models
Plotting
`check.overlap()`	Check propensity score overlap
`plot(<subgroup_fitted>)` `plot(<subgroup_validated>)`	Plotting results for fitted subgroup identification models
`plotCompare()`	Plot a comparison results for fitted or validated subgroup identification models
Summarizing
`summarize.subgroups()`	Summarizing covariates within estimated subgroups
`summary(<subgroup_fitted>)` `summary(<wksvm>)`	Summary of results for fitted subgroup identification models
`print(<subgroup_fitted>)` `print(<subgroup_validated>)` `print(<subgroup_summary>)`	Printing results for fitted subgroup identification models
`print(<individual_treatment_effects>)`	Printing individualized treatment effects
`subgroup.effects()`	Computes treatment effects within various subgroups
`treatment.effects()` `treat.effects()`	Calculation of covariate-conditional treatment effects
Predicting
`predict(<subgroup_fitted>)` `predict(<wksvm>)`	Function to predict either benefit scores or treatment recommendations
Data
`LaLonde`	National Supported Work Study Data
Utilities
`create.propensity.function()`	Creation of propensity fitting function
`create.augmentation.function()`	Creation of augmentation functions
`weighted.ksvm()`	Fit weighted kernel svm model.

Reference