Adjusting for Misclassification: A Three-Phase Sampling Approach
- Autores: Hailin Sang, Kenneth K. Lopiano, Denise A. Abreu, Andrea C. Lamas, Pam Arroway, Linda J. Young
- Localización: Journal of official statistics, ISSN 0282-423X, Vol. 33, Nº. 1, 2017, págs. 207-222
- Idioma: inglés
- DOI: 10.1515/jos-2017-0011
- Enlaces
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Resumen
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.
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