“Likelihood-Based Inference for Generalized Linear Mixed Models: Inference with R Package glmm.” Slides prepared for the 2020 Symposium on Data Science and Statistics.

“Bayesian Methods for Data Science in R.” Slides prepared for the 2020 Symposium on Data Science and Statistics.

“Intro to Bayesian Statistics” at the Conference on Statistical Practice 2020 in Sacramento, CA.

“Revisiting the Gelman-Rubin Diagnostic.” Slides prepared for the Conference on Statistical Practice 2020 in Sacramento, CA.

“Inference for Generalized Linear Mixed Models.” Slides prepared for the Conference on Statistical Practice 2020 in Sacramento, CA.

“Revisiting the Gelman-Rubin Diagnostic.” Slides prepared for BayesComp 2020 at the University of Florida.

“Be a Person, Not a Number Cruncher.” Slides prepared for the 2019 Women in Data Science Symposium at the University of Minnesota.

“Revisiting the Gelman-Rubin Diagnostic.” Slides prepared for Women in Statistics and Data Science 2019 in Bellevue, Washington.

“Revisiting the Gelman-Rubin Diagnostic: Improved Stability and a Principled Threshold.” Slides prepared for Symposium on Data Science and Statistics 2019 in Bellevue, Washington.

“Inference for Generalized Linear Mixed Models.” Slides prepared for Women in Statistics and Data Science 2018 in Cincinnati, Ohio.

“Monte Carlo likelihood approximation: accounting for ‘it’s not you; it’s me.'” Slides prepared for my invited talk at the University of Minnesota (Monte Carlo, statistics, and so much more: a conference in honor of Charlie Geyer) in April 2018.

“An Introduction to Developing R Packages” materials that Haema Nilakanta, Lindsey Dietz, and I prepared for Women in Statistics and Data Science (2017) in La Jolla, California:

“R Package glmm: Likelihood-Based Inference for Generalized Linear Mixed Models” slides prepared for useR!2017 in Brussels, Belgium.