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Adjusting for Misclassification: A Three-Phase Sampling Approach Cover

Adjusting for Misclassification: A Three-Phase Sampling Approach

Open Access
|Feb 2017

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 prescreening process and from field-estimating farm status for nonresponse 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 nonresponse adjustment for the second phase (ALUS). A design-unbiased estimator of the variance is provided in explicit form.

Language: English
Page range: 207 - 222
Submitted on: May 1, 2014
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Accepted on: Oct 1, 2016
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Published on: Feb 21, 2017
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2017 Hailin Sang, Kenneth K. Lopiano, Denise A. Abreu, Andrea C. Lamas, Pam Arroway, Linda J. Young, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.