AUC_zeros: Impute zero delay/100% likely indifference points

In discAUC: Linear and Non-Linear AUC for Discounting Data

Impute zero delay/100% likely indifference points

Description

As defined by Myerson et al. (2001) the indifference point at 0 delay (100% likelihood) is set to 0. This function will add that indifference point, wherever it is missing. If the 0 delay (100% likelihood) is included in the data then it will not be overwritten.

Usage

AUC_zeros(dat, indiff, x_axis, amount, groupings = NULL, prob_disc = FALSE)

Arguments

dat	Discounting data tibble
indiff	Indifference points Variable
x_axis	Delays/probabilities/social distance variable
amount	Amount of the larger delayed/probablistic/etc. outcome (A in discounting formulas)
groupings	Variables for grouping (e.g., subject, expeirmental group) as a character or vector of characters
prob_disc	Boolean for probability discounting, if set to true function will calculate and report odds against x_axis

Value

Tibble that is grouped by groupings but in the same order as supplied to the function. If prob_disc == FALSE, then the function will add indifference points of amount at x_axis = 0. If prob_disc == TRUE, then the function will add indifference points of amount at x_axis = 1. Additionally, a orig column will be added to indicate whether the indifference point was included in the data or was imputed.

Examples

AUC_zeros(
  examp_DD,
  indiff = "prop_indiff",
  x_axis = "delay_months",
  amount = 1,
  groupings = c("subject", "outcome")
)

AUC_zeros(
  examp_PD,
  indiff = "prop_indiff",
  x_axis = "prob",
  amount = 1,
  groupings = c("subject", "outcome"),
  prob_disc = TRUE
)

discAUC documentation built on March 31, 2023, 5:26 p.m.