11 citations · 11 across the 5 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
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…
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…
Testing weak nulls in matched observational studies
Colin B. Fogarty
We develop sensitivity analyses for weak nulls in matched observational studies while allowing unit-level treatment effects to vary. The methods may be applied to studies using any…