| CausalState-package | CausalState: Causal Inference in a Longitudinal Transitioning State Environment |
| absorb_rule | Define an absorbing-state override rule |
| branch_cal_summary | Per-time, per-branch calibration summary from an SDR or iTMLE fit |
| CausalState | CausalState: Causal Inference in a Longitudinal Transitioning State Environment |
| contrast | Compute contrasts between two fitted estimators |
| density_ratio | Estimate density ratios for a modified treatment policy |
| itmle | Infinite-dimensional TMLE (iTMLE) estimator for longitudinal MTPs |
| method.WB_dr | Wu-Benkeser log-density-ratio metalearner for SuperLearner |
| print.branch_cal_summary | Print methods for CausalState output objects |
| print.itmle_fit | Print methods for CausalState output objects |
| print.qreg_fit | Print methods for CausalState output objects |
| print.sdr_fit | Print methods for CausalState output objects |
| qreg | Pure Q-recursion estimator - diagnostic use only |
| sdr | Sequential Doubly Robust (SDR) estimator for longitudinal MTPs |
| sim_bin | Simulated ICU panel with a single binary treatment |
| sim_cont | Simulated ICU panel with a single continuous treatment |
| sim_multi | Simulated ICU panel with multiple treatments (any mix of binary + continuous) |
| SL.tgt.empty | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tgt.glm | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tgt.glmnet | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tgt.intercept | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tgt.xgboost | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_empty | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_glm | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_glmnet_enet | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_glmnet_lasso | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_glmnet_ridge | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_intercept | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_xgb_d1 | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_xgb_d3 | Custom SuperLearner wrappers for the iTMLE targeting step |
| SL.tmle_xgb_d6 | Custom SuperLearner wrappers for the iTMLE targeting step |
| sl_itmle | Custom SuperLearner wrappers for the iTMLE targeting step |
| sl_tmle | Default SuperLearner library for the iTMLE targeting step |
| weight_diagnostics | Per-time weight diagnostics for a density ratio object |