Package index

All functions

abcd_data

Simulated data from AntiBiotics for Children with severe Diarrhea (ABCD) trial

aiptw_tes()

Function to estimate treatment effects using AIPTW for external data

apply_OTR()

Function to apply existing OTR(s) to external data

average_across_seeds()

Helper function to average results across multiple seeds

calc_aiptw()

Function to calculate AIPTW

compare.otr_results()

Compare outcomes under different treatment rules

compute_estimates()

Make treatment decisions and compute estimated outcomes/treatment effects

compute_estimates_external()

Function to compute estimates on external dataset

estimate_OTR()

Main function to calculate estimated treatment effects for treatment rule

learn_CATE()

Function to learn model for CATE using k-fold cross validation

learn_nuisance()

Estimate nuisance models (outcome, treatment, and missingness) and calculate CATE hats using k-fold cross validation

predict(<avgSuperLearner>)

Method to average predictions over multiple SuperLearners

predict_CATE_external()

Function to predict CATEs & get treatment decisions on external dataset

print(<average_results>)

Print the output of a "average_results" object.

print(<full_otr_results>)

Print the output of a "full_otr_results" object.

print(<otr_comparison>)

Print the results of otr_comparison

print(<otr_results>)

Print the output of a "full_otr_results" object.

strip_cate()

Helper function to apply strip_glm function to libraries in CATE model

strip_glm()

Helper function to remove unnecessary output from SuperLearner model to reduce output size

strip_nuisance()

Helper function to apply strip_glm function to libraries in Nuisance model