Physical Sciences and Mathematics Commons^™

Combining Survey And Non-Survey Data For Improved Sub-Area Prediction Using A Multi-Level Model, Jae Kwang Kim, Zhonglei Wang, Zhengyuan Zhu, Nathan B. Cruze

Zhengyuan Zhu

Combining information from different sources is an important practical problem in survey sampling. Using a hierarchical area-level model, we establish a framework to integrate auxiliary information to improve state-level area estimates. The best predictors are obtained by the conditional expectations of latent variables given observations, and an estimate of the mean squared prediction error is discussed. Sponsored by the National Agricultural Statistics Service of the US Department of Agriculture, the proposed model is applied to the planted crop acreage estimation problem by combining information from three sources, including the June Area Survey obtained by a probability-based sampling of lands, administrative …