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20212023
most citedA Bayesian hierarchical small-area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial Census data

3 citations · 3 across the 7 of their papers we have counts for

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6 papers · 1 filter

stat.ME2023

Pseudo-Bayesian unit level modeling for small area estimation under informative sampling

Peter A. Gao, Jon Wakefield

When mapping subnational health and demographic indicators, direct weighted estimators of small area means based on household survey data can be unreliable when data are limited. I…

stat.ME2023

Adaptive Gaussian Markov Random Fields for Child Mortality Estimation

Serge Aleshin-Guendel, Jon Wakefield

The under-5 mortality rate (U5MR), a critical health indicator, is typically estimated from household surveys in lower and middle income countries. Spatio-temporal disaggregation o…

stat.ME2023

Small Area Estimation with Random Forests and the LASSO

Victoire Michal, Jon Wakefield, Alexandra M. Schmidt +3

We consider random forests and LASSO methods for model-based small area estimation when the number of areas with sampled data is a small fraction of the total areas for which estim…

stat.ME2022

Spatial Aggregation with Respect to a Population Distribution

John Paige, Geir-Arne Fuglstad, Andrea Riebler +1

Spatial aggregation with respect to a population distribution involves estimating aggregate quantities for a population based on an observation of individuals in a subpopulation. I…

stat.ME20213 cited

A Bayesian hierarchical small-area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial Census data

Emily N Peterson, Rachel C Nethery, Tullia Padellini +6

Small area estimates of population are necessary for many epidemiological studies, yet their quality and accuracy are often not assessed. In the United States, small area estimates…

stat.ME2021

Statistical implications of relaxing the homogeneous mixing assumption in time series Susceptible-Infectious-Removed models

Luis D. J. Martinez Lomeli, Michelle N. Ngo, Jon Wakefield +2

Infectious disease epidemiologists routinely fit stochastic epidemic models to time series data to elucidate infectious disease dynamics, evaluate interventions, and forecast epide…