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09/08/2023
Commentary on Guyll et al. (2023): Misuse of Statistical Method Results in Highly Biased Interpretation of Forensic Evidence
Since the National Academy of Sciences released their report outlining p...
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08/23/2023
Consistency of common spatial estimators under spatial confounding
This paper addresses the asymptotic performance of popular spatial regre...
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04/27/2023
Augmented balancing weights as linear regression
We provide a novel characterization of augmented balancing weights, also...
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04/04/2023
Graphical Models of Entangled Missingness
Despite the growing interest in causal and statistical inference for set...
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03/09/2023
Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects
An important strategy for identifying principal causal effects, which ar...
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01/19/2022
Prospective Learning: Back to the Future
Research on both natural intelligence (NI) and artificial intelligence (...
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02/11/2021
Clarifying causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects
This paper aims to contribute to helping practitioners of causal mediati...
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11/18/2020
Clarifying causal mediation analysis for the applied researcher: Effect identification via three assumptions and five potential outcomes
Causal mediation analysis is complicated with multiple effect definition...
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11/09/2020
Identifying effects of multiple treatments in the presence of unmeasured confounding
Identification of treatment effects in the presence of unmeasured confou...
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07/09/2020
Causal Effects in Twin Studies: the Role of Interference
The use of twins designs to address causal questions is becoming increas...
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01/17/2020
Counterexamples to "The Blessings of Multiple Causes" by Wang and Blei
This brief note is meant to complement our previous comment on "The Bles...
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10/11/2019
Comment on "Blessings of Multiple Causes"
The premise of the deconfounder method proposed in "Blessings of Multipl...
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07/30/2019
Network Dependence and Confounding by Network Structure Lead to Invalid Inference
Researchers across the health and social sciences generally assume that ...
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12/12/2018
Causal inference, social networks, and chain graphs
Traditionally, statistical and causal inference on human subjects relies...
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10/09/2017