add_effect_diagnostic | Add an additional diagnostic to the effect model |
add_effect_model | Add an additional model to the joint effect ensemble |
add_known_propensity_score | Uses a known propensity score |
add_moderator | Adds moderators to the configuration |
add_outcome_diagnostic | Add an additional diagnostic to the outcome model |
add_outcome_model | Add an additional model to the outcome ensemble |
add_propensity_diagnostic | Add an additional diagnostic to the propensity score |
add_propensity_score_model | Add an additional model to the propensity score ensemble |
add_vimp | Adds variable importance information |
attach_config | Attach an 'HTE_cfg' to a dataframe |
basic_config | Create a basic config for HTE estimation |
calculate_ate | Calculates a SATE and a PATE using AIPW |
calculate_diagnostics | Calculate diagnostics |
calculate_linear_vimp | Calculate Linear Variable Importance of HTEs |
calculate_pcate_quantities | Calculate "partial" CATE estimates |
calculate_rroc | Regression ROC Curve calculation |
calculate_vimp | Calculate Variable Importance of HTEs |
check_data_has_hte_cfg | Checks that a dataframe has an attached configuration for... |
check_identifier | Checks that an appropriate identifier has been provided |
check_nuisance_models | Checks that nuisance models have been estimated and exist in... |
check_splits | Checks that splits have been properly created. |
check_weights | Checks that an appropriate weighting variable has been... |
Constant_cfg | Configuration of a Constant Estimator |
construct_pseudo_outcomes | Construct Pseudo-outcomes |
Diagnostics_cfg | Configuration of Model Diagnostics |
estimate_diagnostic | Function to calculate diagnostics based on model outputs |
estimate_QoI | Estimate Quantities of Interest |
fit_effect | Fits a treatment effect model using the appropriate settings |
fit_fx_predictor | Fit a predictor for treatment effects |
fit_plugin | Fits a plugin model using the appropriate settings |
fit_plugin_A | Fits a propensity score model using the appropriate settings |
fit_plugin_Y | Fits a T-learner using the appropriate settings |
FX.Predictor | Predictor class for the cross-fit predictor of "partial"... |
HTE_cfg | Configuration of Quantities of Interest |
HTEFold | R6 class to represent partitions of the data between training... |
KernelSmooth_cfg | Configuration for a Kernel Smoother |
Known_cfg | Configuration of Known Model |
listwise_deletion | Removes rows which have missing data on any of the supplied... |
make_splits | Define splits for cross-fitting |
MCATE_cfg | Configuration of Marginal CATEs |
Model_cfg | Base Class of Model Configurations |
Model_data | R6 class to represent data to be used in estimating a model |
PCATE_cfg | Configuration of Partial CATEs |
predict.SL.glmnet.interaction | Prediction for an SL.glmnet object |
produce_plugin_estimates | Estimate models of nuisance functions |
QoI_cfg | Configuration of Quantities of Interest |
remove_vimp | Removes variable importance information |
SLEnsemble_cfg | Configuration for a SuperLearner Ensemble |
SL.glmnet.interaction | Elastic net regression with pairwise interactions |
SLLearner_cfg | Configuration of SuperLearner Submodel |
split_data | Partition the data into folds |
Stratified_cfg | Configuration for a Stratification Estimator |
tidyhte-package | tidyhte: Tidy Estimation of Heterogeneous Treatment Effects |
VIMP_cfg | Configuration of Variable Importance |
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