Package: tidyhte 1.0.2

tidyhte: Tidy Estimation of Heterogeneous Treatment Effects

Estimates heterogeneous treatment effects using tidy semantics on experimental or observational data. Methods are based on the doubly-robust learner of Kennedy (n.d.) <arxiv:2004.14497>. You provide a simple recipe for what machine learning algorithms to use in estimating the nuisance functions and 'tidyhte' will take care of cross-validation, estimation, model selection, diagnostics and construction of relevant quantities of interest about the variability of treatment effects.

Authors:Drew Dimmery [aut, cre, cph]

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tidyhte.pdf |tidyhte.html✨
tidyhte/json (API)
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Peer review:

Bug tracker:https://github.com/ddimmery/tidyhte/issues

On CRAN:

32 exports 13 stars 1.69 score 37 dependencies 11 scripts 968 downloads

Last updated 1 years agofrom:21b553ae05. Checks:OK: 5 NOTE: 2. Indexed: yes.

Exports:add_effect_diagnosticadd_effect_modeladd_known_propensity_scoreadd_moderatoradd_outcome_diagnosticadd_outcome_modeladd_propensity_diagnosticadd_propensity_score_modeladd_vimpattach_configbasic_configConstant_cfgconstruct_pseudo_outcomesDiagnostics_cfgestimate_diagnosticestimate_QoIHTE_cfgKernelSmooth_cfgKnown_cfgmake_splitsMCATE_cfgModel_cfgModel_dataPCATE_cfgproduce_plugin_estimatesQoI_cfgremove_vimpSL.glmnet.interactionSLEnsemble_cfgSLLearner_cfgStratified_cfgVIMP_cfg

Dependencies:backportsbitopscaToolscheckmateclicodetoolscrayoncvAUCdata.tabledplyrfansiforeachgamgenericsgluegplotsgtoolshmsiteratorsKernSmoothlifecyclemagrittrnnlspillarpkgconfigprettyunitsprogresspurrrR6rlangROCRSuperLearnertibbletidyselectutf8vctrswithr