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Sensitivity to unmeasured confounding is not typically a primary consideration in designing treated-control comparisons in observational studies.
Minimax linear estimation of the retargeted mean
Hirshberg, D. A., A. Maleki, and J. R. Zubizarreta (2019) · 1901
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Discussion of ‘Randomization analysis of experimental data: The Fisher randomization test comment’ by Basu
Rubin, D. B. (1980) · 1980
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Van der Vaart, A. W. (2000) · 2000
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Design sensitivity in observational studies
Rosenbaum, P. R. (2004) · 2004
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Doubly robust estimation in missing data and causal inference models
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Heterogeneity and causality: Unit heterogeneity and design sensitivity in observational studies
Rosenbaum, P. R. (2005) · 2005
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A distributional approach for causal inference using propensity scores
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Kang, J. D. and J. L. Schafer (2007) · 2007
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Heller, R., P. R. Rosenbaum, and D. S. Small (2009) · 2009
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What aspects of the design of an observational study affect its sensitivity to bias from covariates that were not observed?
Rosenbaum, P. R. (2011) · 2011
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Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies
Hainmueller, J. (2012) · 2012
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Hsu, J. Y., D. S. Small, and P. R. Rosenbaum (2013) · 2013
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Bahadur efficiency of sensitivity analyses in observational studies
Rosenbaum, P. R. (2015) · 2015
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Stable weights that balance covariates for estimation with incomplete outcome data
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Sharp sensitivity analysis for inverse propensity weighting via quantile balancing
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The uniform general signed rank test and its design sensitivity
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Interpretable sensitivity analysis for balancing weights
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Sensitivity analysis without assumptions
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Sensitivity analysis in observational research: introducing the e-value
VanderWeele, T. J. and P. Ding (2017) · 2017
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Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores
Yang, S. and P. Ding (2018) · 2018
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Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Zhao, Q., D. S. Small, and B. B. Bhattacharya (2019) · 2019
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Making Sense of Sensitivity: Extending Omitted Variable Bias
Cinelli, C. and C. Hazlett (2020) · 2020
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Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations
Wang, Y. and J. R. Zubizarreta (2020) · 2020
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Variance-based sensitivity analysis for weighting estimators result in more informative bounds
Huang, M. and S. D. Pimentel (2022) · 2022
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Sensitivity analysis under the f f -sensitivity models: Definition, estimation and inference
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From” is it unconfounded?” to” how much confounding would it take?”: Applying the sensitivity-based approach to assess causes of support for peace in colombia
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Kernel conditional moment constraints for confounding robust inference
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