5 papers
A scalable Bayesian double machine learning framework, with application to racial disproportionality assessment
Yu Luo, Vanessa McNealis, Yijing Li
Racial disproportionality in stop and search practices elicits substantial concerns about its societal and behavioral impacts. In London, Black individuals are about four times mor…
Smoothed pseudo-population bootstrap methods with applications to finite population quantiles
Vanessa McNealis, Christian Léger
This paper introduces smoothed pseudo-population bootstrap methods for the purposes of variance estimation and the construction of confidence intervals for finite population quanti…
Plasmode simulation for the evaluation of causal inference methods in homophilous social networks
Vanessa McNealis, Erica E. M. Moodie, Nema Dean
Typical simulation approaches for evaluating the performance of statistical methods on populations embedded in social networks may fail to capture important features of real-world…
Joint mixed-effects models for causal inference in clustered network-based observational studies
Vanessa McNealis, Erica E. M. Moodie, Nema Dean
Causal inference on populations embedded in social networks poses technical challenges, since the typical no interference assumption frequently does not hold. Existing methods deve…
Revisiting the Effects of Maternal Education on Adolescents' Academic Performance: Doubly Robust Estimation in a Network-Based Observational Study
Vanessa McNealis, Erica E. M. Moodie, Nema Dean
In many contexts, particularly when study subjects are adolescents, peer effects can invalidate typical statistical requirements in the data. For instance, it is plausible that a s…