I graduated from the University of Kansas with a Ph.D. in Research, Evaluation, Measurement, & Statistics. My research ranges from the development of new statistical modeling techniques to the application of tried-and-true techniques.

A full list of my publications can be found in my CV, and you can also check out my Google Scholar profile, though it’s less complete. To see some non-paywalled research work, I’ve provided some of my conference presentations on this website.

My research during my Ph.D. focused on Item Response Theory, Differential Item Functioning, and hierarchical modeling. My dissertation, Finding Item-Level Causes of Differential Item Functioning: A Hierarchical IRT Model for Explaining DIF, combined all those subjects plus Bayesian estimation and an added dash of explanatory modeling.

I also use a variety of other statistical techniques for my daily psychometric and data science work: linear regressions, logistic regressions, ANOVAs, structural equation models, decision trees, classical test theory analyses, exploratory and confirmatory factor analyses, and meta-analyses.