Evaluating Heterogeneous Treatment Effects

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Documentation for package ‘evalHTE’ version 0.1.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

compute_qoi	Compute Quantities of Interest (GATE, GATEcv, URATE)
compute_qoi_user	Compute Quantities of Interest (GATE, GATEcv, URATE) 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
estimate_hte	Evaluate Heterogeneous Treatment Effects
evaluate_hte	Evaluate Heterogeneous Treatment Effects
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
plot.hte	Plot the GATE estimate
plot_CI	Plot Confidence Intervals
plot_CI.hte	Plot the uniform confidence interval
print.summary.hte	Print
print.summary.test_hte	Print
summary.hte	Summarize Heterogeneity and Consistency Tests
summary.test_hte	Summarize Heterogeneity and Consistency Tests
test_itr	Conduct hypothesis tests
URATE	This function use individualized treatment rule to identify exceptional responders. The details of the methods for this design are given in Imai and Li (2023).