data_adapt {adaptest} | R Documentation

## S3-Style Constructor for Data Adaptive Parameter Class

### Description

S3-Style Constructor for Data Adaptive Parameter Class

### Usage

    data_adapt(Y, A, W = NULL, n_top, n_fold, absolute, negative,
      parameter_wrapper, learning_library)

### Arguments

`Y` | (numeric vector) - continuous or binary biomarkers outcome variables
`A` | (numeric vector) - binary treatment indicator: `1` = treatment, `0` = control
`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 `FALSE`, test for directional effect. This overrides argument `negative`.
`negative` | (logical) - whether or not to test for negative effect size. If `FALSE` = test for positive effect size. This is effective only when `absolute = FALSE`.
`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 `rank_DE`.
`learning_library` | (character vector) - library of learning algorithms to be used in fitting the "Q" and "g" step of the standard TMLE procedure.

### Value

`S3` object of class "data_adapt" for data-adaptive multiple testing.

[Package adaptest version 1.2.0 Index]