Josh Nugent, PhD

Biostatistician at the Kaiser Permanente Division of Research focusing on causal inference, machine learning, and clustered data. Before earning my doctorate (advised by Laura Balzer), I was a high school math teacher for 8 years, among other things. I have also worked frequently with the SEARCH Collaboration, evaluating impacts of various interventions to reduce infectious disease burden in Kenya and Uganda.

Research interests & expertise:

• Causal inference with applications to public health, medicine, and public policy
• Semiparametric statistics with discrete or continuous exposures
• Integrating (ensemble) machine learning and statistical inference via targeted learning
• Design and analysis of randomized trials, particularly with small samples and complex dependence structures
• Interpretation and communication of statistical results
• Teaching statistical concepts
• Anti-racism, equity, inclusion, social justice, conflict resolution

Publications

Please see my Google Scholar profile for the most up-to-date publication list.

Informal projects, explainers, experiments, visualizations, etc…

• Inspired by the recent arrival of a nephew, an analysis of state-level patterns in newborn names and future name popularity prediction. Summary of some 2020 findings and Shiny app in development to explore the data.

• Vignette on adjusting settings, trying different optimizers, and/or using the allFit() function to help achieve convergence in lmer/glmer mixed models. At least one person (not me) has used this to save their dissertation research from failure!