calc_aucs: Calculate Area-Under-the-Curve (AUC) Metrics for Delay Discounting Data
Description
This function calculates three types of Area-Under-the-Curve (AUC) metrics for delay discounting data:
regular AUC (using raw delays), log10 AUC (using logarithmically scaled delays), and ordinal AUC (using ordinally scaled delays).
These metrics provide different perspectives on the rate of delay discounting.
Usage
calc_aucs(dat)
Value
A tibble with the following columns:
id: The participant or group identifier.
auc_regular: The regular AUC, calculated using the raw delay values.
auc_log10: The log10 AUC, calculated using logarithmically transformed delay values.
auc_rank: The rank AUC, calculated using ordinally scaled delay values.
Arguments
dat
A data frame containing delay discounting data.
It must include the following columns:
id: Participant or group identifier.
x: Delay values (e.g., in days).
y: Indifference point values (e.g., subjective value of the delayed reward).
# Example datadata <- data.frame(
id = rep("P1", 6),
x = c(1, 7, 30, 90, 180, 365),
y = c(0.8, 0.5, 0.3, 0.2, 0.1, 0.05)
)
# Calculate AUC metrics for a single participantcalc_aucs(data)