Function reference • evalITR

All functions

AUPEC(): Estimation of the Area Under Prescription Evaluation Curve (AUPEC) in Randomized Experiments

AUPECcv(): Estimation of the Area Under Prescription Evaluation Curve (AUPEC) in Randomized Experiments Under Cross Validation

compute_qoi(): Compute Quantities of Interest (PAPE, PAPEp, PAPDp, AUPEC, GATE, GATEcv)

compute_qoi_user(): Compute Quantities of Interest (PAPE, PAPEp, PAPDp, AUPEC, GATE, GATEcv) with user defined functions

consist.test(): The Consistency Test for Grouped Average Treatment Effects (GATEs) in Randomized Experiments

consistcv.test(): The Consistency Test for Grouped Average Treatment Effects (GATEs) under Cross Validation in Randomized Experiments

create_ml_args(): Create general arguments

create_ml_args_bart(): Create arguments for bartMachine

create_ml_args_bartc(): Create arguments for bartCause

create_ml_args_causalforest(): Create arguments for causal forest

create_ml_args_lasso(): Create arguments for LASSO

create_ml_args_superLearner(): Create arguments for super learner

create_ml_args_svm(): Create arguments for SVM

create_ml_args_svm_cls(): Create arguments for SVM classification

create_ml_arguments(): Create arguments for ML algorithms

estimate_itr(): Estimate individual treatment rules (ITR)

evaluate_itr(): Evaluate ITR

fit_itr(): Estimate ITR for Single Outcome

GATE(): Estimation of the Grouped Average Treatment Effects (GATEs) in Randomized Experiments

GATEcv(): Estimation of the Grouped Average Treatment Effects (GATEs) in Randomized Experiments Under Cross Validation

het.test(): The Heterogeneity Test for Grouped Average Treatment Effects (GATEs) in Randomized Experiments

hetcv.test(): The Heterogeneity Test for Grouped Average Treatment Effects (GATEs) under Cross Validation in Randomized Experiments

PAPD(): Estimation of the Population Average Prescription Difference in Randomized Experiments

PAPDcv(): Estimation of the Population Average Prescription Difference in Randomized Experiments Under Cross Validation

PAPE(): Estimation of the Population Average Prescription Effect in Randomized Experiments

PAPEcv(): Estimation of the Population Average Prescription Effect in Randomized Experiments Under Cross Validation

PAV(): Estimation of the Population Average Value in Randomized Experiments

PAVcv(): Estimation of the Population Average Value in Randomized Experiments Under Cross Validation

plot(<itr>): Plot the AUPEC curve

plot_estimate(): Plot the GATE estimate

print(<summary.itr>): Print

print(<summary.test_itr>): Print

star: Tennessee’s Student/Teacher Achievement Ratio (STAR) project

summary(<itr>): Summarize estimate_itr output

summary(<test_itr>): Summarize test_itr output

test_itr(): Conduct hypothesis tests