Dr. Brumback’s recent methodological research investigates methods for causal inference with complex survey data. She has been particularly interested in methods for adjusting for unmeasured cluster-level confounding with complex sampling designs. This has led to the development of new methods stemming from conditional likelihood techniques, generalized linear mixed models, and structural nested models. She also collaborates with investigators in other disciplines across the health sciences.