dips: Decisions in Preference Systems

Code and data for an MSc project titled: Following the leader? Group movement in a socially living African ground squirrel

Monte Carlo simulations to support decision making

Personalised eczema treatment recommendations

Balloon Analog Risk Task (PsychoPy) and data processing (R)

This is my first R task during my Masters. The file contain UK Data Police in West Yorkshire about street criminal crimes from Jan 2020 - Sep 2021 and the objective of this task is to find interesting facts within this data.

Research project investigating the addition of confidence bounds to the drift diffusion model (DDM) in order to explain confidence ratings and their associated reaction times.

By using the Analytical Hierarchy Process (AHP) in tandem with landscape metrics, we can determine which parcel is best suited for restoration! Use my shiny app as a template to create your own interactive site selection shiny app!

Using R, I delve into two given datasets to conduct statistical analysis to help a company in its decision-making process.

Exploring one iconic task in decision making research

Analyses scripts used for Algermissen, J. & den Ouden, H. E. (2024). Pupil dilation reflects effortful action invigoration in overcoming aversive Pavlovian biases. Cognitive, Affective, & Behavioral Neuroscience

For files & code related to the EDI study ("Effort, Decision-making, and Interoception").

Analyses scripts used for Algermissen, J. & den Ouden, H. E. (2023). Goal-directed recruitment of Pavlovian biases through selective visual attention. Journal of Experimental Psychology: General.

Analyses scripts used for Algermissen, J. & den Ouden, H. E. M. (2024). High stakes slow responding, but do not help overcome Pavlovian biases in humans. Learning & Memory.

Task timing and preference analysis

Application Web for Health Economics Decision Making

R software package for describing, explaining, simulating and predicting human decision making.

Emma Fox R/Shiny Project with a docker server configuration

This repository contains the code for the paper "Infection Rate Models for COVID-19: Model Risk and Public Health News Sentiment Exposure Adjustments", by Ioannis Chalkiadakis, Kevin Hongxuan Yan, Gareth W. Peters, Pavel V. Shevchenko.

Replication of simulations and results from Chapelle, O., & Li, L. (2011). An empirical evaluation of Thompson sampling. Advances in neural information processing systems, 2249-2257.