Dr. David Vock

PUBHL Biostatistics Division
School of Public Health
Twin Cities
Project Title: 
Methods for Causal Interference and Dynamic Treatment Regimes

This group develops novel computational tools to estimate the causal effect of an intervention or action. Particular interests include:

  • Variable selection techniques for causal inference
  • Methods when the intervention is reported with error (e.g., compliance)
  • Power formula for developing a dynamic treatment regime
  • Methods to improve SMART designs

Project Investigators

Charles Cain
Chuyu Deng
Grace Lyden
Ross Peterson
Aparajita Sur
Dr. David Vock
Jack Wolf
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