The lab has a few general areas of focus, listed below along with a brief motivation, description of current work, and some more recent papers.
Treatment effect variation
Characterizing treatment variation in general is a difficult problem, but is integral to getting the most out of large-scale randomized trials.
Multisite experiments are very common in education, and provide great opportunity in that they are actually a collection of small randomized experiments with many shared properties. By leveraging this view, we can ask how treatment varies across site and attempt to understand more about the reasons a treatment may, or may not have been successful.
Geographic regression discontinuity designs
Geographic regression discontinuity focuses on looking at how to analyze data where a geographic border separates units who have been treated from units who have not been. By focusing one's attention to units on either side of the border, we can hope to understand the impact of treatment, or provide sharper comparisons of differences in the two regions, controlling for other characteristics.
Text data, with a focus on causality
Text data are increasingly ubiquitous in the modern era. (Consider, for example, internet forums, newspapers, or student essays.) But text is high dimensional and messy and complex. Therefore, analyzing contexts where text is considered a covariate or outcome becomes tricky.