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stat.ME2025
Sensitivity of weighted least squares estimators to omitted variables
Leonard Wainstein, Chad Hazlett
We introduce tools for assessing the sensitivity, to unobserved confounding, of a common estimator of causal effects that employs weights: the weighted linear regression of the out…
stat.ME2025
Inference with weights: Residualization produces short, valid intervals for varying estimands and varying resampling processes
Erin Hartman, Chad Hazlett, Arisa Sadeghpour
Weighting procedures are used in observational causal inference to adjust for covariate imbalance within the sample. Common practice for inference is to estimate robust standard er…
stat.ME2025
Post-treatment problems: What can we say about the effect of a treatment among sub-groups who (would) respond in some way?
Chad Hazlett, Nina McMurry, Tanvi Shinkre
Investigators are often interested in how a treatment affects an outcome for units responding to treatment in a certain way. We may wish to know the effect among units that, for ex…