1 citations · 1 across the 4 of their papers we have counts for
5 papers
Prediction-Powered Smoothing and Validation for Disaggregated AI Evaluation
Sho Kawano, Zehang Richard Li, Paul A. Parker
Evaluating an AI system requires disaggregated assessment, as performance varies across domains such as benchmark task types or conversation types in deployed agents. Exhaustive te…
Nonprobability Samples for Small Area Estimation: A Review and Comparative Simulation Study
Sho Kawano, Daniel Vedensky, Qianyu Dong +5
Nonprobability samples (NPS) are attractive because they are less costly to collect, can provide substantially larger sample sizes, and may reach populations that traditional proba…
sae4health: An R Shiny Application for Small Area Estimation in Low- and Middle-Income Countries
Yunhan Wu, Qianyu Dong, Jieyi Xu +2
Accurate subnational estimation of health indicators is critical for public health planning, particularly in low- and middle-income countries (LMICs), where data and analytic tools…
Toward a Principled Workflow for Prevalence Mapping Using Household Survey Data
Qianyu Dong, Yunhan Wu, Zehang Richard Li +1
Understanding the prevalence of key demographic and health indicators in small geographic areas and domains is of global interest, especially in low- and middle-income countries (L…
Spatially Selected and Dependent Random Effects for Small Area Estimation with Application to Rent Burden
Sho Kawano, Paul A. Parker, Zehang Richard Li
Area-level models for small area estimation typically rely on areal random effects to shrink design-based direct estimates towards a model-based predictor. Incorporating the spatia…