Combining Information from Multiple Surveys by using Regression for Efficient Small Domain Estimation

DOI10.1111/j.1467-9868.2009.00724.xzbMath1411.62033OpenAlexW1973422203MaRDI QIDQ4632619

T. Merkouris

Publication date: 30 April 2019

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9868.2009.00724.x

zbMATH Keywords

calibrationauxiliary informationsmall area estimationcomposite estimatorgeneralized regression estimatorrare populations

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Sampling theory, sample surveys (62D05)

Related Items (8)

Statistical data integration in survey sampling: a review ⋮ Small area estimation combining data from two surveys ⋮ Empirical Likelihood Approach for Aligning Information from Multiple Surveys ⋮ Design‐based Estimators Calibrated on Estimated Totals from Multiple Surveys ⋮ A measurement error model approach to survey data integration: combining information from two surveys ⋮ Combining Data from New and Traditional Sources in Population Surveys ⋮ A global optimisation approach to range-restricted survey calibration ⋮ Combining survey and non-survey data for improved sub-area prediction using a multi-level model

This page was built for publication: Combining Information from Multiple Surveys by using Regression for Efficient Small Domain Estimation