build_augbin_data: Build a dataset of class '"augbin_data"'
In mjg211/augbin: Augmented Binary Method for Analysing Responder Outcomes

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/build_augbin_data.R

Builds a dataset of class "augbin_data", principally for use with augbin.

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build_augbin_data(continuous = stats::rnorm(100),
  binary = stats::rbinom(100, 1, 0.4), treatment = stats::rbinom(100,
  1, 0.5), dichotomisation = 0, summary = FALSE)

`continuous`	A `numeric` `vector` containing the observations of a continuous component of a responder outcome. Each element should correspond to the observation for a different patient.
`binary`	A `numeric` `vector` containing the observations of a binary failure component of a responder outcome. Each element of `binary` must be either 0 or 1 and its `length` should be equal to that of `continuous`. In addition, its elements should be ordered such that the observation for a particular patient is in the same position as it is in `continuous`.
`treatment`	A `numeric` `vector` containing the treatment assignments. Each element of `treatment` must be either 0 (corresponding to the 'control' arm) or 1 (corresponding to the 'experimental' arm). In addition, its elements should be ordered such that the treatment assignment for a particular patient is in the same position as it is in `continuous`.
`dichotomisation`	A `numeric` giving the dichotomisation hreshold for the continuous component (see `continuous`). A patient is a responder if their binary component (see `binary`) is 0 and their continuous component is below `dichotomisation`.

The responder outcome is assumed to define a responder when a continuous component (see continuous) is below a particular dichotomisation threshold (see dichotomisation) and a binary component (see binary) is 0.

A tibble, with additional class "augbin_data".

Michael J Grayling.

augbin, print.augbin, summary.augbin, plot.augbin.