14 citations · 15 across the 7 of their papers we have counts for
6 papers · 1 filter
A Bayesian Multiscale Integrated Abundance Model for Estimating Latent Opioid Misuse Prevalence from Spatially Misaligned Data
Staci A. Hepler, Brian N. White, Magdalena Cerda +3
Estimating small area prevalence of opioid misuse is critical for targeting public health interventions, yet direct measures are unavailable and related surveillance data are often…
Bayesian Nonparametric Approaches to Ordinal Drought Modeling in the United States
Mostafa Shams, Robert Erhardt, Staci Hepler
Data observed over space and time can exhibit dependence across both dimensions, and datasets can grow very large in both the number of locations and the number of time periods. Th…
Three Case Studies of Two-stage MCMC for Fast Bayesian Inference of Large Spatio-temporal Data
Mostafa Shams, Robert Erhardt, Staci Hepler
High dimensional spatio-temporal models can quickly run up against computational limitations. Recursive or multi-stage Bayesian algorithms are one way to address this computational…
Two-stage MCMC for Fast Bayesian Inference of Large Spatio-temporal Ordinal Data, with Application to US Drought
Staci Hepler, Rob Erhardt
High dimensional space-time data pose known computational challenges when fitting spatio-temporal models. Such data show dependence across several dimensions of space as well as in…
The `Why' behind including `Y' in your imputation model
Lucy D'Agostino McGowan, Sarah C. Lotspeich, Staci A. Hepler
Missing data is a common challenge when analyzing epidemiological data, and imputation is often used to address this issue. Here, we investigate the scenario where a covariate used…
An integrated abundance model for estimating county-level prevalence of opioid misuse in Ohio
Staci A. Hepler, David Kline, Andrea Bonny +2
Opioid misuse is a national epidemic and a significant drug related threat to the United States. While the scale of the problem is undeniable, estimates of the local prevalence of…