PHIE propagates uncertainty from HB domain posteriors to cross-tabulations via chi-square calibrated replicate weights, with tiered Calibrated Bayes intervals restoring near-nominal coverage and showing that uncertainty stems mainly from compositional sampling variability.
More with Less: Bethel Allocation and Precision-Preserving Sample Size Reduction via Hierarchical Bayes Modelling
2 Pith papers cite this work. Polarity classification is still indexing.
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DMM design cuts sample size from 42,018 to 40,251 while achieving 100% movement precision coverage versus 82-96% for classical design in 2021 Australian Census simulations.
citing papers explorer
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Post-Hoc Inference of Cross-Classified Statistics from Hierarchical Bayes Survey Weights
PHIE propagates uncertainty from HB domain posteriors to cross-tabulations via chi-square calibrated replicate weights, with tiered Calibrated Bayes intervals restoring near-nominal coverage and showing that uncertainty stems mainly from compositional sampling variability.
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Dynamic Mini Max Design and Sequential HB Inference for Repeated Surveys
DMM design cuts sample size from 42,018 to 40,251 while achieving 100% movement precision coverage versus 82-96% for classical design in 2021 Australian Census simulations.