EPIC-lab

Evaluating Policy Implications with Causal-inference

Welcome to the EPIC-Lab

Does participation in an after-school tutoring programme cause better marks? Simple observation might show participants have higher scores, but these students might also be more motivated or have more supportive parents. Distinguishing the programme’s true effect from background factors is the central challenge of evaluation. EPIC-Lab (Evaluating Policy Implications with Causal-inference) is designed to solve this problem. We pair the rigorous logic of causal inference with the predictive power of machine learning to quantify whether interventions work, for whom they are most effective, and under which circumstances they provide benefit. Our work delivers robust answers to urgent questions in psychological science and public policy. EPIC-Lab is based at the School of Psychological Science at Victoria University of Wellington (Te Herenga Waka), New Zealand.

Our Mission

  1. Advance causal inference in the social sciences, both in observational research and experimental design.
  2. Educate scholars through hands‑on training in modern causal methods
  3. Promote evidence-based decision making through robust causal workflows and collaboration with experts.

Research Focus

Causal Methods in Social Science

  • stating clear causal questions
  • doubly robust machine learning
  • causal forests and heterogeneous treatment effects
  • longitudinal modified treatment policies (multi-exposures)

Application Domains

  • volunteering/charity
  • institutional trust
  • individual differences
  • religion

Resources

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NoteRecent News

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