I’m a PhD student at York University’s Quantitative Methods program in the Psychology Department. I am interested in equivalence testing, accuracy in parameter estimation, effect sizes, and Monte Carlo simulations. In addition, I’m very passionate about teaching statistics, data science, programming, and philosophy of science. I strongly advocate for open-science practices, replicable and reproducible research, and I am an avid R user.
PhD, Quantitative Methods, in progress
York University
MA, Psychology (focus on quantitative psychology), 2021
Ryerson University
BSc, Specialized Honours, Psychology and Neuroscience, 2016
York University
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.