Abstract: Heterogeneous effects are ubiquitous in the social sciences and are often an important component of---and means of assessing---theoretical arguments. A common strategy to assess this heterogeneity is to include a single multiplicative interaction term between the treatment and a hypothesized effect moderator in a regression model. In this paper, we show how inferences about interactions under this approach are highly sensitive to modeling choices about how the effect modifier interacts with other covariates, an issue almost never discussed in practice.  We...

Read more about Matt Blackwell presents "On Model Dependence in the Estimation of Interactive Effects"

Covariate adjustment is often used for estimation of population average causal effects (ATE). In recent years graphical rules have been derived for determining, from a causal diagram, all covariate adjustment sets. Restricting attention to causal linear models, a very recent article introduced two graphical criterions: one to compare the asymptotic variance of linear regression estimators that control for certain distinct adjustment sets and a second to identify the optimal adjustment set that provides the smallest asymptotic variance. In this talk, I will show that the same graphical... Read more about Andrea Rotnitzky presents "Efficient adjustment sets for population average causal effect estimation in graphical models"

Abstract: For complex diseases like depression, choosing a successful treatment from several possible drugs remains a trial-and-error process in current clinical practice. By applying statistical machine learning to the electronic health records of thousands of patients, can we discover subtypes of disease which both improve population-wide understanding and improve patient-specific drug recommendations? One popular approach is to represent noisy, high-dimensional health records as mixtures of low-dimensional subtypes via a probabilistic topic model. I will introduce...

Read more about Michael Hughes presents "Discovering Disease Subtypes that Improve Treatment Predictions: Prediction-Constrained Topic Models for Personalized Medicine"

Abstract: Colonial powers typically organized economic activity in the colonies to maximize  their economic returns. While the literature has emphasized long-run negative economic impacts via institutional quality, the changes in economic organization implemented to spur production historically could also directly influence economic organization in the long-run, exerting countervailing effects. We examine these in the context  of the Dutch Cultivation System, the integrated industrial and agricultural system for producing sugar that formed the core of the Dutch...

Read more about Melissa Dell presents "The Development Effects Of The Extractive Colonial Economy: The Dutch Cultivation System In Java"