Abstract Machine learning has the potential to facilitate the development of computational
methods that improve the measurement of cognitive and mental functioning. In three …

A state-of-the-art data analysis procedure is presented to conduct hierarchical Bayesian
inference and hypothesis testing on delay discounting data. The delay discounting task is a …

A novel method for analyzing delay discounting data is proposed. This newer metric, a
model‐based Area Under Curve (AUC) combining approximate Bayesian model selection …

Original, open‐source computer software was developed and validated against established
delay discounting methods in the literature. The software executed approximate Bayesian …

Delay discounting (DD) and probability discounting (PD) refer to the reduction in the
subjective value of outcomes as a function of delay and uncertainty, respectively. Elevated …

In intertemporal choice research, choice tasks (ie, choosing between 80todayand 100 in a
year) are often used to elicit a discount rate. The discount rate derived from a choice task …

The study of delay discounting, or valuation of future rewards as a function of delay, has
contributed to understanding the behavioral economics of addiction. Accurate …

Delay discounting paradigms have gained widespread popularity across clinical research.
Given the prevalence in the field, researchers have set lofty expectations for the importance …

Delay discounting refers to a decline in the value of a reward when it is delayed relative to
when it is immediately available. Delay discounting tasks are used to identify indifference …

The tendency to discount the value of future rewards has become one of the best-studied
constructs in the behavioral sciences. Although hyperbolic discounting remains the …