D
Daniel Westreich
Researcher at University of North Carolina at Chapel Hill
Publications - 181
Citations - 7378
Daniel Westreich is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Population & Pregnancy. The author has an hindex of 36, co-authored 165 publications receiving 5492 citations. Previous affiliations of Daniel Westreich include Duke University & University of the Witwatersrand.
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Journal ArticleDOI
Illustrating bias due to conditioning on a collider
Stephen R. Cole,Robert W. Platt,Enrique F. Schisterman,Haitao Chu,Daniel Westreich,David B. Richardson,Charles Poole +6 more
TL;DR: This work provides two hypothetical examples to convey concepts underlying bias due to conditioning on a collider, or collider-stratification, bias, which is a common effect of a genotype and an environmental factor.
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Doubly Robust Estimation of Causal Effects
Michele Jonsson Funk,Daniel Westreich,Chris Wiesen,Til Stürmer,M. Alan Brookhart,Marie Davidian +5 more
TL;DR: The authors present a conceptual overview of doubly robust estimation, a simple worked example, results from a simulation study examining performance of estimated and bootstrapped standard errors, and a discussion of the potential advantages and limitations of this method.
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The Table 2 Fallacy: Presenting and Interpreting Confounder and Modifier Coefficients
TL;DR: Suggestions are offered to limit potential misunderstandings when multiple effect estimates are presented, including precise distinction between total and direct effect measures from a single model, and use of multiple models tailored to yield total-effect estimates for covariates.
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Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
TL;DR: Boosting and, to a lesser extent, decision trees appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice.
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Invited Commentary: Positivity in Practice
Daniel Westreich,Stephen R. Cole +1 more
TL;DR: In this article, the authors define positivity, distinguish between deterministic and random positivity and discuss the 2 relevant papers in this issue, and illustrate positivity in simple 2 × 2 tables, as well as detail some ways in which epidemiologists may examine their data for non-positivity and deal with violations of positivity.