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06/18/2023
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
In this article we develop a feasible version of the assumption-lean tes...
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02/08/2023
Potential Outcome and Decision Theoretic Foundations for Statistical Causality
In a recent paper published in the Journal of Causal Inference, Philip D...
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12/21/2022
The role of grace periods in comparative effectiveness studies of different medications
Researchers are often interested in estimating the effect of sustained u...
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07/20/2022
Global sensitivity analysis for studies extending inferences from a randomized trial to a target population
When individuals participating in a randomized trial differ with respect...
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05/19/2022
Deep Learning Methods for Proximal Inference via Maximum Moment Restriction
The No Unmeasured Confounding Assumption is widely used to identify caus...
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03/28/2022
Randomized trials and their observational emulations: a framework for benchmarking and joint analysis
A randomized trial and an analysis of observational data designed to emu...
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08/25/2021
Nonparametric identification is not enough, but randomized controlled trials are
We argue that randomized controlled trials (RCTs) are special even among...
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03/03/2021
Discussion of 'Estimating time-varying causal excursion effect in mobile health with binary outcomes' by T. Qian et al
We discuss the recent paper on "excursion effect" by T. Qian et al. (202...
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08/13/2020
An Interventionist Approach to Mediation Analysis
Judea Pearl's insight that, when errors are assumed independent, the Pur...
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08/13/2020
Multivariate Counterfactual Systems And Causal Graphical Models
Among Judea Pearl's many contributions to Causality and Statistics, the ...
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08/07/2020
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
This is the rejoinder to the discussion by Kennedy, Balakrishnan and Was...
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07/28/2020
Estimation of local treatment under the binary instrumental variable model
Instrumental variables are widely used to deal with unmeasured confoundi...
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06/28/2020
Conditional separable effects
Researchers are often interested in treatment effects on outcomes that a...
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05/01/2020
A Formal Causal Interpretation of the Case-Crossover Design
The case-crossover design (Maclure, 1991) is widely used in epidemiology...
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04/30/2020
Generalized interpretation and identification of separable effects in competing event settings
In competing event settings, a counterfactual contrast of cause-specific...
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08/27/2019
Efficient estimation of optimal regimes under a no direct effect assumption
We derive new estimators of an optimal joint testing and treatment regim...
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06/29/2019
Identification In Missing Data Models Represented By Directed Acyclic Graphs
Missing data is a pervasive problem in data analyses, resulting in datas...
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06/26/2019
Generalizing causal inferences from randomized trials: counterfactual and graphical identification
When engagement with a randomized trial is driven by factors that affect...
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05/25/2019
Sensitivity analysis using bias functions for studies extending inferences from a randomized trial to a target population
Extending (generalizing or transporting) causal inferences from a random...
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05/19/2019
Study designs for extending causal inferences from a randomized trial to a target population
We examine study designs for extending (generalizing or transporting) ca...
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04/08/2019
On assumption-free tests and confidence intervals for causal effects estimated by machine learning
For many causal effect parameters ψ of interest doubly robust machine le...
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04/07/2019
A unifying approach for doubly-robust â„“_1 regularized estimation of causal contrasts
We consider inference about a scalar parameter under a non-parametric mo...
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04/07/2019
Characterization of parameters with a mixed bias property
In this article we characterize a class of parameters in large non-param...
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01/28/2019
Separable Effects for Causal Inference in the Presence of Competing Risks
In time-to-event settings, the presence of competing events complicates ...
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11/17/2014
Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations
We propose and analyze estimators for statistical functionals of one or ...
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09/26/2013
Sparse Nested Markov models with Log-linear Parameters
Hidden variables are ubiquitous in practical data analysis, and therefor...
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07/20/2012
Parameter and Structure Learning in Nested Markov Models
The constraints arising from DAG models with latent variables can be nat...
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03/15/2012
On the Validity of Covariate Adjustment for Estimating Causal Effects
Identifying effects of actions (treatments) on outcome variables from ob...
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02/14/2012
