Over the years I've needed to create custom functions in R and scripts in Python to accomplish very specific tasks. Although few folks will face the same difficulties, I will be adding these utilities I have needed to create to this page in hopes that it will save someone hours of headache! Feel free to reach out to me at email@example.com with questions.
Drift Diffusion Model Prep for R - I created this script while working on my dissertation. In short, DDM is a very complex analysis that requires a good deal of prep work for the data, as each participant's data are analyzed separately and must be in individual files. This script assumes you will be using fast-dm to apply the DDM.
intPlot for R - This is a function I created for making interactive network plots for psychometric networks. The code is still a bit clunky, so instead of just posting the function code here I've linked to my blog post that walks through a few examples - the code for these examples is available via links in the post and can be readily adapted to any network that was estimated using bootnet or qgraph.
Participant-level Sentiment Analysis in R - Ever used an essay-writing task or manipulation? Want to know exactly what kind of emotions your participants are expressing in their writing? This script is for you! This analysis routine makes use of the syuzhet package for R and allows researchers who have collected essay or other text data in Qualtrics or similar platforms (e.g., SurveyMonkey) to quickly and conveniently extract participant-level scores for specific emotions expressed in their writing. Specifically, this code results in a dataset containing your participant numbers and their scores for anger, anticipation, fear, joy, sadness, surprise, trust, and two general affective valence scores: positive and negative. Full tutorial on how to apply this cool technique coming soon!