Description Usage Arguments Value

S3-Style Constructor for Data Adaptive Parameter Class

1 2 | ```
data_adapt(Y, A, W = NULL, n_top, n_fold, absolute, negative,
parameter_wrapper, learning_library)
``` |

`Y` |
(numeric vector) - continuous or binary biomarkers outcome variables |

`A` |
(numeric vector) - binary treatment indicator: |

`W` |
(numeric vector, numeric matrix, or numeric data.frame) - matrix of baseline covariates where each column correspond to one baseline covariate. Each row correspond to one observation |

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

`n_fold` |
(integer vector) - number of cross-validation folds. |

`absolute` |
(logical) - whether or not to test for absolute effect size.
If |

`negative` |
(logical) - whether or not to test for negative effect size.
If |

`parameter_wrapper` |
(function) - user-defined function that takes input
(Y, A, W, absolute, negative) and outputs a (integer vector) containing
ranks of biomarkers (outcome variables). For detail, please refer to the
documentation for |

`learning_library` |
(character vector) - library of learning algorithms to be used in fitting the "Q" and "g" step of the standard TMLE procedure. |

`S3`

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

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