I am currently working at the intersection of population health and healthcare strategy, leveraging medical data (claims and EHR) to improve patient outcomes and reduce costs at Boston Medical Center. Previously, I spent time building and managing a team of data scientists at McKinsey & Company, focusing on workforce and organizational analytics for clients across a variety of industries.
I received my Ph.D in 2015 from the Quantitative Psychology program at the University of Virginia, where I worked with Brian Nosek, Sara Rimm-Kaufman, and Timo von Oertzen on projects focusing on quantitative challenges found in applied educational research. I also participated in the July 2015 Insight Health Data Science program in Boston.
My interests include statistics, machine learning, education, and open science. If you look around, you will find some blog posts, publications, and relevant code. You can also see a copy of my resume here.
IAT: Contains a dplyr implementation of the D-Score algorithm for the Implicit Association Test, as well as plotting functions to visualize the raw data from these tests.
Ebersole, C. R. et al. (2016). Many Labs 3: Evaluating participant pool quality across the academic semester via replication. Journal of Experimental Social Psychology, 67, 68 – 82.
Koh, K. A. et al. (2020). Health care spending and use among people experiencing unstable housing in the era of Accountable Care Organizations. Health Affairs, 39, 214 – 223.
*Martin, D. P. & von Oertzen, T. (2015). Growth mixture models outperform simpler clustering algorithms when detecting longitudinal heterogeneity, even with small sample sizes. Structural Equation Modeling, 22, 264 – 275.
Martin, D. P., & Rimm-Kaufman, S. E. (2015). Do student self-efficacy and teacher-student interaction quality contribute to emotional and social engagement in fifth grade math? Journal of School Psychology, 53, 359 – 376.
Martin, D. P. (2015). Efficiently exploring multilevel data with recursive partitioning.. (Dissertation)
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349, 943.
Silberzahn R., Uhlmann E. L., Martin D. P., …, & Nosek, B. A. (2018). Many analysts, one dataset: Making transparent how variations in analytical choices affect results. Advances in Methods and Practices in Psychological Science, 1, 337 – 356.
* Fun fact: This publication gave me an Erdös number of 4:
Daniel P. Martin →
Timo von Oertzen →
Peter A. Jonsson →
Pavol Hell →
Paul Erdös
