## Abstract

Background and objective: Delayed rewards are commonly perceived as less valuable than immediate rewards, a phenomenon referred to as either delay discounting or temporal discounting. Here, an adaptive discounting procedure developed for the E-Prime programming environment and an associated analysis script implemented in Excel are described.

Methods: The experimental procedure was developed in E-Prime 2.0.10.242 and an associated analysis workbook in Excel 2013. Area under the curve (AUC) and hyperbolic discounting were used to measure delay discounting.

Results: Example data from a sample (n= 19, mean age 21, 14 females) are presented. There was good agreement between AUC and log k values (hyperbolic) (AUC 100 and logK 100 was r(19) = -.889, p < .001, AUC 1000 and logK 1000, r(19) = -.906, p < .001 and AUC 10000 and logK 10000, r(19) = -.872, p < .001. At the individual level, the fit of the hyperbolic discounting function to the data was generally good (R2 values ranged between .88 and .97)

Conclusions: An adaptive delay discounting procedure within the E-Prime programming environment and an associated analysis script (executed in Excel) are described. This implementation, freely available to the scientific community, may be suited to laboratories with limited programming resources or experience that intend to use this software suite for developing and implementing experimental paradigms.

Methods: The experimental procedure was developed in E-Prime 2.0.10.242 and an associated analysis workbook in Excel 2013. Area under the curve (AUC) and hyperbolic discounting were used to measure delay discounting.

Results: Example data from a sample (n= 19, mean age 21, 14 females) are presented. There was good agreement between AUC and log k values (hyperbolic) (AUC 100 and logK 100 was r(19) = -.889, p < .001, AUC 1000 and logK 1000, r(19) = -.906, p < .001 and AUC 10000 and logK 10000, r(19) = -.872, p < .001. At the individual level, the fit of the hyperbolic discounting function to the data was generally good (R2 values ranged between .88 and .97)

Conclusions: An adaptive delay discounting procedure within the E-Prime programming environment and an associated analysis script (executed in Excel) are described. This implementation, freely available to the scientific community, may be suited to laboratories with limited programming resources or experience that intend to use this software suite for developing and implementing experimental paradigms.

Original language | English |
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DOIs | |

Publication status | Unpublished - 2017 |