About

I am a Behavioural Scientist at Intact Insurance and a PhD candidate in Quantitative Psychology and Modelling at McGill University in the Flake Lab. Here are a few things I've been working on lately:

Professionally:

• Using machine learning to guide interventions to increase customer retention
• Developing software for effect sizes in multilevel models
• Quantifying the impact of decisions in modelling pipelines on result heterogeneity
• Teaching statistical methods for clustered data structures

Personally:

• Chess
• Woodworking (including making a chess board!)
• Cross-country skiing and biking

To connect, feel free to email me at maireadkshaw [at] gmail [dot] com.

Blog Posts

• Which Chess Opening is Best for Your Rating?

Journal Articles

Shaw, M., Rights, J.D., Sterba, S.K., & Flake, J.K. (2022). r2mlm: An R package for computing effect sizes in multilevel models. Behavior Research Methods. https://doi.org/10.3758/s13428-022-01841-4.
 
Sun, S., Shaw, M., Moodie, E., Ruths, D. (2022). The epidemiological impact of the Canadian COVID Alert App. Canadian Journal of Public Health, 113, 519-527. https://doi.org/10.17269/s41997-022-00632-w.
 
Flake, J. K., Luong, R., & Shaw, M. (2022). Addressing a crisis of generalizability with large-scale construct validation. Behavioral and Brain Sciences, 45, e14. https://doi.org/10.1017/S0140525X21000376.
 
Shaw, M., Cloos, L.J.R., Luong, R., Elbaz, S., & Flake, J.K. (2020). Measurement practices in large-scale replications: Insights from Many Labs 2. Canadian Psychology/Psychologie canadienne, 61(4), 289-298. http://dx.doi.org/10.1037/cap0000220. OSF materials.

Teaching Resources

Shaw, M. and Flake, J.K. (2023), Digital Module 34: Introduction to Multilevel Measurement Modeling. Educational Measurement: Issues and Practice, 42: 82-82. https://doi.org/10.1111/emip.12585.
 
Shaw, M. & Flake, J.K. Introduction to Multilevel Modelling, 2022. https://www.learn-mlms.com

Software

Shaw, M., Rights, J.D., Sterba, S.K., & Flake, J.K. (2020). r2mlm: R-Squared Measures for Multilevel Models. R package version 0.3.7. https://CRAN.R-project.org/package=r2mlm

Workshops

(2024, June). Multilevel R-squared Effect Size Measures and Bootstrapped Confidence Intervals. Presented to researchers at Modern Modeling Methods Conference.
 
(2024, January). Introduction to R for Experimental Research. Presented to students at McGill University.
 
(2023, October). Bootstrapping Confidence Intervals for Multilevel Models. Presented to data scientists at industry partner.
 
(2023, March). Effect Sizes in Multilevel Models. Presented to Quantitative Psychology Methodologies Workshop at McGill University.
 
(2022, June). Understanding, calculating, and interpreting R-squared in multilevel models Presented to researchers at Canadian Psychological Association Conference.
 
(2022, March). Understanding, calculating and interpreting R-squared in multilevel models Presented to researchers at McGill University Daily Diary Research Methods Group.

Statistical Consulting

I am available for private statistical consulting. I have worked as a statistical analyst and advisor for a government agency, the McGill Martlets hockey team, and for physician scientists. In these roles, I provided services including but not limited to:

• Helping design analysis plans for funded studies
• Cleaning data to prepare for modelling
• Statistical modelling
• Preparing data visualizations
• Communicating results to non-expert audiences in presentations and reports
• Teaching team members how to conduct their own analyses in R and Python

If you need help with statistics of any kind, feel free to reach out at maireadkshaw [at] gmail [dot] com. I offer free 30-minute consultations to determine the scope of the project. I love hearing about statistical problems, so don't be shy!

As an homage to the website that inspired mine (seandevine.org), I'm including a secret link! (It's not a Rick Roll.) https://www.youtube.com/watch?v=VISC5jRXEIA
 
Link last updated: 2024-10-16