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

weighted.ksvm()

Fit weighted kernel svm model.