Adjusting for Misclassification: A Three-Phase Sampling Approach
Abstract
The United States Department of Agriculture's National Agricultural Statistics Service (NASS) conducts the June Agricultural Survey (JAS) annually. Substantial misclassification occurs during the pre-screening process and from field-estimating farm status for non-response and inaccessible records, resulting in a biased estimate of the number of US farms from the JAS. Here the Annual Land Utilization Survey (ALUS) is proposed as a follow-on survey to the JAS to adjust the estimates of the number of US farms and other important variables. A three-phase survey design-based estimator is developed for the JAS-ALUS with non-response adjustment for the second phase (ALUS). A design-unbiased estimator of the variance is provided in explicit form.
Cite
@article{arxiv.1306.3541,
title = {Adjusting for Misclassification: A Three-Phase Sampling Approach},
author = {Hailin Sang and Kenneth K. Lopiano and Denise A. Abreu and Andrea C. Lamas and Pam Arroway and Linda J. Young},
journal= {arXiv preprint arXiv:1306.3541},
year = {2016}
}
Comments
30 pages, to appear at Journal of Official Statistics