Doubly-Robust Nonparametric Estimation and Inference

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Documentation for package ‘drtmle’ version 1.1.2

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

Help Pages

adaptive_iptw	Compute asymptotically linear IPTW estimators with super learning for the propensity score
average_est_cov_list	Helper function for averaging lists of estimates generated in the main 'for' loop of 'drtmle'
average_ic_list	Helper function to average convergence results and drtmle influence function estimates over multiple fits
ci	Compute confidence intervals for drtmle and adaptive_iptw@
ci.adaptive_iptw	Confidence intervals for adaptive_iptw objects
ci.drtmle	Confidence intervals for drtmle objects
drtmle	TMLE estimate of the average treatment effect with doubly-robust inference
estimateG	estimateG
estimategrn	estimategrn
estimategrn_loop	estimategrn_loop
estimateG_loop	estimateG_loop
estimateQ	estimateQ
estimateQrn	estimateQrn
estimateQrn_loop	estimateQrn_loop
estimateQ_loop	estimateQ_loop
eval_Diptw	Evaluate usual influence function of IPTW
eval_Diptw_g	Evaluate extra piece of the influence function for the IPTW
eval_Dstar	Evaluate usual efficient influence function
eval_Dstar_g	Evaluate extra piece of efficient influence function resulting from misspecification of outcome regression
eval_Dstar_Q	Evaluate extra piece of efficient influence function resulting from misspecification of propensity score
extract_models	Help function to extract models from fitted object
fluctuateG	fluctuateG
fluctuateQ	fluctuateQ
fluctuateQ1	fluctuateQ1
fluctuateQ2	fluctuateQ2
make_validRows	Make list of rows in each validation fold.
partial_cv_preds	Helper function to properly format partially cross-validated predictions from a fitted super learner.
plot.drtmle	Plot reduced dimension regression fits
predict.SL.npreg	Predict method for SL.npreg
print.adaptive_iptw	Print the output of a '"adaptive_iptw"' object.
print.ci.adaptive_iptw	Print the output of ci.adaptive_iptw
print.ci.drtmle	Print the output of ci.drtmle
print.drtmle	Print the output of a '"drtmle"' object.
print.wald_test.adaptive_iptw	Print the output of wald_test.adaptive_iptw
print.wald_test.drtmle	Print the output of wald_test.drtmle
reorder_list	Helper function to reorder lists according to cvFolds
SL.npreg	Super learner wrapper for kernel regression
tmp_method.CC_LS	Temporary fix for convex combination method mean squared error Relative to existing implementation, we reduce the tolerance at which we declare predictions from a given algorithm the same as another
tmp_method.CC_nloglik	Temporary fix for convex combination method negative log-likelihood loss Relative to existing implementation, we reduce the tolerance at which we declare predictions from a given algorithm the same as another. Note that because of the way 'SuperLearner' is structure, one needs to install the optimization software separately.
wald_test	Wald tests for drtmle and adaptive_iptw objects
wald_test.adaptive_iptw	Wald tests for adaptive_iptw objects
wald_test.drtmle	Wald tests for drtmle objects