4 papers
Bayesian inference for disease transmission models informed by viral dynamics
Dylan J. Morris, Lauren Kennedy, Andrew J. Black
Infectious disease dynamics operate across multiple biological scales, with within-host viral dynamics being a key driver of between-host transmission. However, while models that e…
Hypothesizing an effect size by considering individual variation
Andrew Gelman, Amy Krefman, Lauren Kennedy +1
When designing and evaluating an experiment or observational study, it is useful to have a realistic hypothesis regarding the average treatment effect. We present an approach to co…
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.…
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…