Description Usage Arguments Value Author(s)

Performs targeted minimum loss-based estimation (TMLE )of a marginal additive treatment effect of a binary point treatment on an outcome. The data-adaptive algorithm is used to perform variable reduction to avoid the disadvantages associated with multiple testing. INTERNAL USE ONLY.

1 2 3 4 |

`Y` |
continuous or binary outcome variable |

`A` |
binary treatment indicator: |

`W` |
matrix containing baseline covariates |

`n_top` |
integer value for the number of candidate covariates to generate using the data-adaptive estimation algorithm |

`n_fold` |
integer number of folds to be used for cross-validation |

`folds_vec` |
Vector of |

`parameter_wrapper` |
function |

`learning_library` |
character |

`absolute` |
boolean: |

`negative` |
boolean: |

`S3`

object of class "data_adapt" for data-adaptive multiple
testing.

Wilson Cai wcai@berkeley.edu, in collaboration with Alan E. Hubbard, with contributions from Nima S. Hejazi.

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