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05/03/2021
Reconciling design-based and model-based causal inferences for split-plot experiments
The split-plot design assigns different interventions at the whole-plot ...
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04/09/2021
Model-assisted analyses of cluster-randomized experiments
Cluster-randomized experiments are widely used due to their logistical c...
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03/30/2021
Multi-Source Causal Inference Using Control Variates
While many areas of machine learning have benefited from the increasing ...
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01/07/2021
Regression-based causal inference with factorial experiments: estimands, model specifications, and design-based properties
Factorial designs are widely used due to their ability to accommodate mu...
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12/03/2020
Multiply robust estimation of causal effects under principal ignorability
Causal inference concerns not only the average effect of the treatment o...
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10/27/2020
Covariate-adjusted Fisher randomization tests for the average treatment effect
Fisher's randomization test (FRT) delivers exact p-values under the stro...
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09/14/2020
The Frisch–Waugh–Lovell Theorem for Standard Errors
The Frisch–Waugh–Lovell Theorem states the equivalence of the coefficien...
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08/06/2020
Identification of Causal Effects Within Principal Strata Using Auxiliary Variables
In causal inference, principal stratification is a framework for dealing...
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05/18/2020
Is being an only child harmful to psychological health?: Evidence from an instrumental variable analysis of China's One-Child Policy
This paper evaluates the effects of being an only child in a family on p...
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05/18/2020
Is being the only child harmful to psychological health?: Evidence from an instrumental variable analysis of China's One-Child Policy
This paper evaluates the effects of being the only child in a family on ...
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02/27/2020
Assessing causal effects in the presence of treatment switching through principal stratification
Clinical trials focusing on survival outcomes often allow patients in th...
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11/03/2019
Conservative Wasserstein Training for Pose Estimation
This paper targets the task with discrete and periodic class labels (e.g...
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07/24/2019
Sharp bounds on the relative treatment effect for ordinal outcomes
For ordinal outcomes, the average treatment effect is often ill-defined ...
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06/26/2019
Rerandomization and Regression Adjustment
Randomization is a basis for the statistical inference of treatment effe...
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06/05/2019
Measurement errors in the binary instrumental variable model
Instrumental variable methods can identify causal effects even when the ...
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04/04/2019
Randomization tests for peer effects in group formation experiments
Measuring the effect of peers on individual outcomes is a challenging pr...
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03/14/2019
A bracketing relationship between difference-in-differences and lagged-dependent-variable adjustment
Difference-in-differences is a widely-used evaluation strategy that draw...
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03/09/2019
Two paradoxical results in linear models: the variance inflation factor and the analysis of covariance
A result from a standard linear model course is that the variance of the...
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12/28/2018
Rerandomization in 2^K Factorial Experiments
With many pretreatment covariates and treatment factors, the classical f...
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09/19/2018
Randomization Tests for Weak Null Hypotheses
The Fisher randomization test (FRT) is applicable for any test statistic...
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07/04/2018
Randomization Inference for Peer Effects
Many previous causal inference studies require no interference among uni...
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06/20/2018
Regression adjustment in randomized experiments with a diverging number of covariates
Extending R. A. Fisher and D. A. Freedman's results on the analysis of c...
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03/06/2018
Using Survival Information in Truncation by Death Problems Without the Monotonicity Assumption
In some randomized clinical trials, patients may die before the measurem...
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01/02/2018
Combining multiple observational data sources to estimate causal effects
The era of big data has witnessed an increasing availability of multiple...
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12/17/2017
Causal Inference: A Missing Data Perspective
Inferring causal effects of treatments is a central goal in many discipl...
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11/07/2017