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