Proximal confounding bridge functions yield four nonparametric identification strategies and a quadruply robust estimator for path-specific effects under unmeasured confounding.
arXiv preprint arXiv:2009.10982 , year=
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A new adaptive variance estimator for relative sparsity coefficients is introduced that fully utilizes the prior asymptotic normality theorem and incorporates variable selection effects.
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Proximal Path-Specific Inference
Proximal confounding bridge functions yield four nonparametric identification strategies and a quadruply robust estimator for path-specific effects under unmeasured confounding.
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An adaptive variance estimator for relative sparsity
A new adaptive variance estimator for relative sparsity coefficients is introduced that fully utilizes the prior asymptotic normality theorem and incorporates variable selection effects.