collaborators

6 papers

math.ST2026

Gaussian comparison above the median

Colin B. Fogarty

We prove a Gaussian comparison inequality for closed convex sets with reference probability at least 1/2. For centered Gaussian vectors whose covariance matrices are ordered in the…

stat.ME2026

Tilted sensitivity analysis in matched observational studies

Colin B. Fogarty

We present a new procedure for conducting a sensitivity analysis in matched observational studies. For any candidate test statistic, the approach defines tilted modifications depen…

stat.ME2026

Stochastic Sensitivity Analysis for Matched Observational Studies

Mengqi Lin, Colin B. Fogarty, Gongjun Xu

Sensitivity analysis asks how strong unmeasured confounding needs to be to explain away an observational study's conclusion. The conventional approach in matched studies conducts i…

stat.ME2026

Powerful Multivariate Sensitivity Analysis via Sample Splitting in an Observational Study of the Effects of Poverty on Cardiovascular Disease Risk Factors

William Bekerman, Anurag Mehta, Rebecca E. Hasson +3

When assessing the causal effect of an exposure on two or more outcomes in an observational study, a linear combination of outcomes may lessen the sensitivity of a test of the glob…

stat.ME2025

Simultaneous Inference for False Discovery Proportions under Sensitivity Models for Observational Studies

Mengqi Lin, Colin Fogarty

We provide an approach to exploratory data analysis in observational studies with a single intervention and multiple endpoints. In such settings, the researcher would like to explo…

stat.ME2025

Heterogeneous Treatment Effects under Network Interference: A Nonparametric Approach Based on Node Connectivity

Heejong Bong, Colin B. Fogarty, Elizaveta Levina +1

In network settings, interference between units makes causal inference more challenging as outcomes may depend on the treatments received by others in the network. Typical estimand…