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20152022
most citedSensitivity Analysis Without Assumptions

12 citations · 41 across the 11 of their papers we have counts for

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7 papers · 1 filter

math.ST2020

The Frisch--Waugh--Lovell Theorem for Standard Errors

Peng Ding

The Frisch--Waugh--Lovell Theorem states the equivalence of the coefficients from the full and partial regressions. I further show the equivalence between various standard errors.…

math.ST2019

Rerandomization and Regression Adjustment

Xinran Li, Peng Ding

Randomization is a basis for the statistical inference of treatment effects without strong assumptions on the outcome-generating process. Appropriately using covariates further yie…

math.ST20181 cited

Rerandomization in Factorial Experiments

Xinran Li, Peng Ding, Donald B. Rubin

With many pretreatment covariates and treatment factors, the classical factorial experiment often fails to balance covariates across multiple factorial effects simultaneously. Ther…

math.ST2018

Regression adjustment in completely randomized experiments with a diverging number of covariates

Lihua Lei, Peng Ding

Randomized experiments have become important tools in empirical research. In a completely randomized treatment-control experiment, the simple difference in means of the outcome is…

math.ST2017

Bridging Finite and Super Population Causal Inference

Peng Ding, Xinran Li, Luke W. Miratrix

There are two general views in causal analysis of experimental data: the super population view that the units are an independent sample from some hypothetical infinite populations,…

math.ST2016

On the Conditional Distribution of the Multivariate Distribution

Peng Ding

As alternatives to the normal distributions, distributions are widely applied in robust analysis for data with outliers or heavy tails. The properties of the multivariate d…