1 citations · 1 across the 3 of their papers we have counts for
3 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.ME2023
Improving Survey Inference in Two-phase Designs Using Bayesian Machine Learning
Xinru Wang, Anyu Zhu, Lauren Kennedy +2
The two-phase sampling design is a cost-effective strategy widely used in public health research. Analyzing the Phase II sample often involves creating subsample-specific weights.…
stat.ME2022★ 1 cited
Using leave-one-out cross-validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale
Swen Kuh, Lauren Kennedy, Qixuan Chen +1
In recent decades, multilevel regression and poststratification (MRP) has surged in popularity for population inference. However, the validity of the estimates can depend on detail…