8 citations · 17 across the 6 of their papers we have counts for
5 papers · 1 filter
Design Sensitivity and Its Implications for Weighted Observational Studies
Melody Huang, Dan Soriano, Samuel D. Pimentel
Sensitivity to unmeasured confounding is not typically a primary consideration in designing treated-control comparisons in observational studies. We introduce a framework allowing…
Variance-based sensitivity analysis for weighting estimators result in more informative bounds
Melody Huang, Samuel D. Pimentel
Weighting methods are popular tools for estimating causal effects; assessing their robustness under unobserved confounding is important in practice. In the following paper, we intr…
Sensitivity Analysis for Survey Weights
Erin Hartman, Melody Huang
Survey weighting allows researchers to account for bias in survey samples, due to unit nonresponse or convenience sampling, using measured demographic covariates. Unfortunately, in…
Sensitivity Analysis in the Generalization of Experimental Results
Melody Huang
Randomized controlled trials (RCT's) allow researchers to estimate causal effects in an experimental sample with minimal identifying assumptions. However, to generalize or transpor…
Balancing Higher Moments Matters for Causal Estimation: Further Context for the Results of Setodji et al. (2017)
Melody Y. Huang, Brian G. Vegetabile, Lane F. Burgette +2
We expand upon the simulation study of Setodji et al. (2017) which compared three promising balancing methods when assessing the average treatment effect on the treated for binary…