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20142026
most citedRegression adjustment in completely randomized experiments with a diverging number of covariates

43 citations · 354 across the 81 of their papers we have counts for

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Showing 2014 · math.STShow all

5 papers · 2 filters

math.ST2014★ 17 cited

To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias

Peng Ding, Luke Miratrix

"M-Bias," as it is called in the epidemiologic literature, is the bias introduced by conditioning on a pretreatment covariate due to a particular "M-Structure" between two latent f…

math.ST2014★ 9 cited

Qualitative Evaluation of Associations by the Transitivity of the Association Signs

Zhichao Jiang, Peng Ding, Zhi Geng

We say that the signs of association measures among three variables {X, Y, Z} are transitive if a positive association measure between the variable X and the intermediate variable…

math.ST2014★ 10 cited

A paradox from randomization-based causal inference

Peng Ding

Under the potential outcomes framework, causal effects are defined as comparisons between potential outcomes under treatment and control. To infer causal effects from randomized ex…

math.ST2014★ 18 cited

Three Occurrences of the Hyperbolic-Secant Distribution

Peng Ding

Although it is the generator distribution of the sixth natural exponential family with quadratic variance function, the Hyperbolic-Secant distribution is much less known than other…

math.ST2014★ 18 cited

Identifiability of Subgroup Causal Effects in Randomized Experiments with Nonignorable Missing Covariates

Peng Ding, Zhi Geng

Although randomized experiments are widely regarded as the gold standard for estimating causal effects, missing data of the pretreatment covariates makes it challenging to estimate…