Examines how therapeutic relationships affect treatment outcomes in virtual mental health care for depression and anxiety.
Open-Source Scientific Projects
Publicly available research, tools, and teaching materials. Applied industry work is separate.
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Markant, D., Phillips, N.D., Kareev, Y., Avrahami, J. & Hertwig, R. (2018). PsyArXiv.
Examines how competitive pressure affects exploration in uncertain environments and how people learn to adapt their strategies.
Phillips, N.D., Neth, H., Woike, J.K. & Gaissmaier, W. (2017). Judgment and Decision Making, 12(4), 344–368.
Introduces the FFTrees R package and a new class of algorithms for constructing transparent decision trees.
Hintze, A., Phillips, N.D. & Hertwig, R. (2015). Scientific Reports, 5, 13662.
Explores how competition can both enhance and hinder cognitive evolution using agent-based simulations.
Phillips, N.D., Hertwig, R., Kareev, Y. & Avrahami, J. (2014). Cognition, 133(1), 104-119.
Examines how competitive environments affect information search and decision-making strategies.
González Vallejo, C., Cheng, J., Phillips, N.D., Chimeli, J., Bellezza, F., Harman, J. & Lindberg, M.J. (2014). Journal of Behavioral Decision Making, 27(3), 209-225.
Tests primacy effects in sequential evaluation and a dynamic judgment model.
González-Vallejo, C. & Phillips, N.D. (2010). Judgment and Decision Making, 5(3), 200-206.
Evaluates claims about unconscious thinking benefits in expert prediction tasks.
Lassiter, G.D., Lindberg, M.J., González-Vallejo, C., Bellezza, F.S. & Phillips, N.D. (2009). Psychological Science, 20(6), 671-675.
Challenges findings on unconscious decision-making with an alternative explanation.
An R package for creating, visualizing, and applying fast-and-frugal decision trees — simple, transparent algorithms for classification in high-stakes domains like medicine. Published in academic journals and used in healthcare and legal decision-making research.
An R package enabling end-to-end electronic health record (EHR) analyses in a cohesive, user-centric platform. Replaced thousands of lines of undocumented SQL/SAS code with simple, human-readable R pipelines — from database connections to derived variables to statistical analyses to visualizations. Empowered both expert data scientists and coding-insecure users to work directly with real-world oncology data.
An R package companion to 'YaRrr! The Pirate's Guide to R'. Contains datasets, functions, and templates for learning R programming and data analysis with a pirate theme.
An R package for survival analysis with a focus on intuitive syntax and visualization. Provides tools for Kaplan-Meier curves, Cox proportional hazards models, and survival data exploration.
A free, open-source introductory textbook for learning R and data science. Written with humor and clarity, it has been used by thousands of students and professionals worldwide as an accessible entry point to statistical programming.