Jeroen Mulder is an affiliated postdoctoral researcher at Utrecht University and Karolinska Institutet with a decade of experience developing and evaluating longitudinal data analysis methods focused on causal inference. He bridges methodological rigor and applied impact by comparing g-methods from epidemiology with structural equation approaches used in psychology and by incorporating machine learning for propensity score estimation. His current NWO Rubicon-funded work tackles temporal misalignment in longitudinal data, and he has explored continuous-time modeling and G-estimation during a visiting scholarship in Berlin. Jeroen prioritizes accessibility—writing clear papers, building user-friendly tools, and teaching researchers at all levels—so methods are actually usable in practice. Outside academia he’s an engaging communicator (TEDx speaker, radio presenter, and cabaret performer), a trait that makes his statistical presentations unusually approachable.
10 years of coding experience
Bachelor of Science (BSc) Communication Science (CW), Bachelor of Science (BSc) Communication Science (CW) at University of Twente
Master of Science (MSc) Statistics, Master of Science (MSc) Statistics at Utrecht University
This repository has been transferred to jeroendmulder.github.io/RI-CLPM for easier maintenance. The Github Pages automatically redirects to the new Github Page.
Contributions:21 commits in 10 months
panel-datalavaanredirectsmpluslongitudinal-data
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.