| adaptive_iptw | Compute asymptotically linear IPTW estimators with super learning for the propensity score |
| 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 |
| estimateQ | estimateQ |
| estimateQrn | estimateQrn |
| 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 |
| fluctuateG | fluctuateG |
| fluctuateQ | fluctuateQ |
| fluctuateQ1 | fluctuateQ1 |
| fluctuateQ2 | fluctuateQ2 |
| 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 |
| SL.npreg | Super learner wrapper for kernel regression |
| 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 |