I am a PhD student in the Quantitative Methods program at York University’s Psychology Department. My research interests include equivalence testing, Bayesian statistics, multilevel modeling, item response theory, and multiplicity control. I also explore the attitudes and practices surrounding open science, software, and statistics. I’m passionate about teaching statistics and a big R fan. As an advocate for open science, I strive to promote research that’s replicable and reproducible.
PhD, Quantitative Methods, in progress
York University
MA, Psychology (focus on quantitative psychology), 2021
Toronto Metropolitan University
BSc, Specialized Honours, Psychology and Neuroscience, 2016
York University
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The purpose of this workshop is to demonstrate how to write safe, effective, and intuitive R code for Monte Carlo simulation experiments containing one or more simulation factors. A few of the attractive Monte Carlo simulation coding strategies we will cover are how to write code which is intuitive to read, write, and debug; how to take advantage of SimDesign’s built-in features for creating flexible and extensible simulations; computational efficiency; reproducibility at the macro and micro level; safe and reliable code execution.