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Code for "Risk and loss aversion and attitude to COVID and vaccines in anxious individuals" by Ferrari, Alexander and Seriès (2023).

R 0.89% Jupyter Notebook 97.09% Python 0.91% MATLAB 1.12%
computational-modelling computational-psychiatry drift-diffusion-model prospect-theory risk-aversion

rlac's Introduction

Overview

This repository contains the data and code needed to reproduce the results from the paper "Risk and loss aversion and attitude to COVID and vaccines in anxious individuals" by by Filippo Ferrari, Jesse Alexander and Peggy Seriès (2023).

Requirements

  • JASP version 0.17.0
  • R version 3.6.3
  • hBayesDM version 1.2.1
  • Stan version 2.21.7
  • HDDM version 0.8.0 (and python 3.6 for it)

Data

  • data_anx_gad7_prior.csv contains the individual demographic and fitted parameters for the data split according to a GAD-7 score median split of the data.
  • data_anx_gad7_prior_hddm.csv is the same asdata_anx_gad7_prior.csv but with the HDDMs parameter estimates from the atvz hddm model included.
  • data_single_prior.csv contains the individual demographic and fitted parameters for the data fitted using a single prior encompassing all participants.
  • hbayesdm_data contains the individual choice data processed to be used by hBayesDm.

JASP

The JASP file contains the entire statistical analysis reported in the paper. data_anx_gad7_prior_hddm.jasp contains the statistical analysis of the HDDMs parameter estimates.

R

The fit_all.r script fits all hBayesDm models used in the paper. It reports MCMC fitting checks, models comparison and reproduces fig.2 in the paper.

HDDMs

The fit_all.py script fits all the HDDMS models used in the paper. The analysis_ and winning_model_atvz notebooks contain the analysis on the HDDMs parameter estimates.

rlac's People

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