Methodological Research Interests

Health Policy: My current interests mostly lie in the exploration of the intersection between causal inference and health policy. Cost data are often subject to right-censoring, which creates some odd complications due to the stochastic nature of cost accrual rates. I seek to address challenges associated with time-varying treatment and confounding in cost and cost-effectiveness analysis, while also dealing with incomplete data and time-updating death risk.

Endogeneity Bias: Nonrandom medication use in observational studies not only acts as a contaminant for estimating associations of interest, but renders many modern causal inference methods inapplicable due to the dubious nature of the ‘no unmeasured confounding’ assumption. There are certain modeling approaches based on 1970s structural equation methodology that can deal with these problems quite nicely…if you’re willing to tolerate some parametric assumptions! I work on relaxing these parametric assumptions to the extent possible without compromising interpretability.

HIV Vaccine Studies: A vaccine to protect against HIV would undoubtedly be a major advance in public health research. One way to screen out ineffective vaccines in a timely fashion would be to identify an immunological marker that can serve as a surrogate of protection from infection. Pilot animal studies can help achieve this goal. I seek to develop statistical methods that account for within-subject correlation to foster studies that are substantially powered to detect minimally clinically relevant effects and surrogate value. After all, a study with no hope of detecting a clinically important result is just as wasteful as a study that can reliably detect one that is clinically meaningless.


I have interests in a wide array of application areas, including (but certainly not limited to) cardiovascular disease, endometrial cancer, immunology, neurology, and urology. My favorite applications often involve disease detection and diagnosis.