2 papers
stat.ME2026
When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
Swen Kuh, Lauren Kennedy, Qixuan Chen +1
When estimating population prevalence from a non-random sample, it is important to adjust for differences between sample and population. However, adjustment for multiple factors re…
stat.AP2026
Multilevel Regression and Poststratification Interface: An Application to Track Community-level COVID-19 Viral Transmission
Yajuan Si, Toan Tran, Jonah Gabry +2
We present a novel Bayesian workflow for multilevel regression and poststratification (MRP), introducing extensions to time-varying data and granular geography and publicly availab…