Hunger increases delay discounting of food and non-food rewards

This repository contains data and analysis code for the paper:

Skrynka, J., & Vincent, B. T. (2019). Hunger increases delay discounting of food and non-food rewards. Psychonomic Bulletin and Review https://doi.org/10.3758/s13423-019-01655-0

This paper is open access, but we provide a pre-print of the author accepted manuscript on PsyArXiv

Data

• data/discounting/ files in this folder correspond to the raw delay discounting choice data
• data/data.csv contains participant data for both conditions, including the subjective hunger measures.

Analyses

The analyses were conducted in Python and are presented in the form of a number of Jupyter notebooks in the analysis folder. These can be viewed online (either on the OSF or in GitHub).

1. analysis/01_subjective_hunger.ipynb Analysis of subjective hunger
2. analysis/02_score_discounting_data.ipynb Bayesian scoring of raw discounting data
3. analysis/03_analyse-hyperbolic.ipynb Analysis of hyperbolic discount function
4. analysis/04_analyse_hypotheses_hyperbolic_logk.ipynb Evaluate hypotheses based on hyperbolic discount function
5. analysis/05_analyse_AUC.ipynb Analysis of AUC from multiple discount functions
6. analysis/06_model_comparison.ipynb Comparison of different discount functions
7. Evaluate hypotheses based on AUC from multiple discount functions Evaluate hypotheses based on AUC from multiple discount functions

Running these notebooks will produce a series of outputs which are also contained in the analysis folder. These outputs are primarily generated figures or generated data stored in .csv files.

There is also a .jasp file which includes Bayesian repeated measures t-tests. This filetype should be viewable online, but can also be viewed and explored in the JASP software available from https://jasp-stats.org.

Packages used

We used the following Python packages

• pandas
• numpy
• matplotlib
• scipy
• dabest: https://github.com/ACCLAB/DABEST-python
• seaborn
• PyMC3: https://github.com/pymc-devs/pymc3