Augmented Inverse Probability Weighting

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Documentation for package ‘AIPW’ version 0.6.9.2

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

Help Pages

AIPW	Augmented Inverse Probability Weighting (AIPW)
AIPW_base	Augmented Inverse Probability Weighting Base Class (AIPW_base)
AIPW_nuis	Augmented Inverse Probability Weighting (AIPW) uses tmle or tmle3 as inputs
AIPW_tmle	Augmented Inverse Probability Weighting (AIPW) uses tmle or tmle3 as inputs
aipw_wrapper	AIPW wrapper function
eager_sim_obs	Simulated Observational Study
eager_sim_rct	Simulated Randomized Trial
fit	Fit the data to the AIPW object
fit.AIPW	Fit the data to the AIPW object
plot.ip_weights	Plot the inverse probability weights using truncated propensity scores by exposure status
plot.p_score	Plot the propensity scores by exposure status
Repeated	Repeated Crossfitting Procedure for AIPW
repfit	Fit the data to the AIPW object repeatedly
repfit.Repeated	Fit the data to the AIPW object repeatedly
stratified_fit	Fit the data to the AIPW object stratified by 'A' for the outcome model
stratified_fit.AIPW	Fit the data to the AIPW object stratified by 'A' for the outcome model
summary	Summary of the average treatment effects from AIPW
summary.AIPW_base	Summary of the average treatment effects from AIPW
summary_median	Summary of the 'repeated_estimates' from 'repfit()' in the Repeated object using median methods.
summary_median.Repeated	Summary of the 'repeated_estimates' from 'repfit()' in the Repeated object using median methods.