augbin: Augmented binary method

In mjg211/augbin: Augmented Binary Method for Analysing Responder Outcomes

Description

Fits the augmented binary method, using an underlying two-component latent variable model.

Usage

augbin(data = build_augbin_data(), summary = FALSE)

Arguments

data	A dataset to analyse. Must be an object of class "augbin_data". See build_augbin_data for further details. Defaults to build_augbin_data().
summary	A logical variable indicating whether to print a summary of the functions progress. Defaults to FALSE.

Details

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

Value

A list of additional class "augbin", to enable use with several available S3 functions. It will contain two components:

• A tibble in the slot "odds_ratio" with three columns, giving the estimated odds ratio and the limits of its 95% confidence interval.

• A list in the slot "inputs", containing each of the input variable.

Author(s)

James MS Wason, Michael J Grayling.

See Also

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

Examples

# Use the augmented binary method on a randomly generated dataset
odds_ratio <- augbin()

mjg211/augbin documentation built on Dec. 7, 2019, 12:28 a.m.