5 citations · 7 across the 5 of their papers we have counts for
9 papers
Characterizing patterns in police stops by race in Minneapolis from 2016-2021
Tuviere Onookome-Okome, Jonah Gorondensky, Eric Rose +3
The murder of George Floyd centered Minneapolis, Minnesota, in conversations on racial injustice in the US. We leverage open data from the Minneapolis Police Department to analyze…
Causal inference: critical developments, past and future
Erica EM Moodie, David A Stephens
Causality is a subject of philosophical debate and a central scientific issue with a long history. In the statistical domain, the study of cause and effect based on the notion of `…
Privacy-preserving estimation of an optimal individualized treatment rule : A case study in maximizing time to severe depression-related outcomes
Erica EM Moodie, Janie Coulombe, Coraline Danieli +2
Estimating individualized treatment rules - particularly in the context of right-censored outcomes - is challenging because the treatment effect heterogeneity of interest is often…
Causal inference under mis-specification: adjustment based on the propensity score
David A. Stephens, Widemberg S. Nobre, Erica E. M. Moodie +1
We study Bayesian approaches to causal inference via propensity score regression. Much of the Bayesian literature on propensity score methods have relied on approaches that cannot…
Double robust estimation of partially adaptive treatment strategies
Denis Talbot, Erica EM Moodie, Caroline Diorio
Precision medicine aims to tailor treatment decisions according to patients' characteristics. G-estimation and dynamic weighted ordinary least squares (dWOLS) are double robust sta…
General Regression Methods for Respondent-Driven Sampling Data
Mamadou Yauck, Erica E. M. Moodie, Herak Apelian +5
Respondent-Driven Sampling (RDS) is a variant of link-tracing sampling techniques that aim to recruit hard-to-reach populations by leveraging individuals' social relationships. As…