Jeff Crukley, PhD
Geek in Charge
Study design*, sample size estimation, power analyses; frequentist and Bayesian modelling/analyses, psychometrics; G Theory; data visualizations, analysis reports and summaries; critical interpretation of literature through a statistical lens; manuscript content, revisions, and presentation support.
Principal component analysis, structural equation modelling, and factor analyses; qualitative/mixed methods**; time series analyses and forecasting, big data analytics through machine learning and deep learning; advanced visualizations, dashboarding; stats teaching, invited talks, and coaching.
*To maximize the quality of your resesarch, consulting a statistician during study design is advised.
**In partnership with Reserca.
Recent Project Examples
Explaining the Effects of Hearing Loss on Emotion Perception
Maddox Hearing Aid Lab, Vanderbilt University
Constructed and validated Bayesian hierarchical multivariate ordinal models to show the effects of communication modality and signal processing on emotion perception. Supported manuscript write-up and revisions.
The TeaChR Study: Teaching Critical Reflection
The Wilson Centre, Toronto General Hospital
Advised design, constructed and validated
Bayesian regression models, and supported write-up of study that demonstrated the effects of teaching approaches on students'
future critically reflective capabilities, measured through their "talk."
Evaluating a Patient as Teacher program
Dept. of Surgery, University of Toronto
Advised design, constructed and validated Bayesian hierarchical multinomial modelling to show the effects of a novel Patient as Teacher program on residents' perceptions of surgeons, provided multiple visualizations and coaching for presentations.
Modelling COVID-19 seroprevalence
Contributing to multiple teams of scientists modelling COVID-19 seroprevalence, nationally to globally.