S3-Style Constructor for Data Adaptive Parameter Class

Source: R/adaptest.R

S3-Style Constructor for Data Adaptive Parameter Class

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.