Description Usage Arguments Value Examples

View source: R/generate_parameter_wrapper.R

Computes ranking of biomarkers based effect sizes, which are computed by
Targeted Minimum Loss-Based Estimation. This function is designed to be
called inside `adaptest`

; it should not be run by itself outside of that
context.

1 2 3 |

`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 corrspond to one baseline covariate. Each row correspond to one observation |

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

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

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

an `integer vector`

containing ranks of biomarkers.

1 2 3 4 5 6 7 8 9 | ```
set.seed(1234)
data(simpleArray)
simulated_array <- simulated_array
simulated_treatment <- simulated_treatment
rank_DE(Y = simulated_array,
A = simulated_treatment,
W = rep(1, length(simulated_treatment)),
absolute = FALSE,
negative = FALSE)
``` |

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