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Row–Column Sampling Design Using Auxiliary Ranking Variables

Author

Listed:
  • Omer Ozturk

    (The Ohio State University)

  • Olena Kravchuk

    (Food and Wine, University of Adelaide)

  • Raymond Correll

    (Food and Wine, University of Adelaide)

Abstract

In this paper, we present a new class of row–column sampling design when a sampling region is presented by non-overlapping quadrats of an rp-by-p row–column grid. Quadrats are rank-ordered on a relevant auxiliary variable, first in the rp rows of the grid and then in the so formed p ranked columns. This ranking enhances the precision of the sampling using ideas from standard rank set sampling methods. The sampling design falls in the traditional sampling framework where the sample selection probabilities are independent of the variables of interest. Selection probabilities are governed by a spatial design and the auxiliary information to facilitate better sampling coverage over the sampling region. The paper constructs unbiased estimators for population mean, total and provides variance estimates for them. It also shows when the new sampling design performs better than its competitors. The new sampling design is applied to a forest and two agricultural field samples to estimate the population means. Supplementary materials accompanying this paper appear online.

Suggested Citation

  • Omer Ozturk & Olena Kravchuk & Raymond Correll, 2022. "Row–Column Sampling Design Using Auxiliary Ranking Variables," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 652-673, December.
    • Handle: RePEc:spr:jagbes:v:27:y:2022:i:4:d:10.1007_s13253-022-00504-3
    DOI: 10.1007/s13253-022-00504-3
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    References listed on IDEAS

    as
    1. Omer Ozturk, 2019. "Two-stage cluster samples with ranked set sampling designs," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(1), pages 63-91, February.
    2. B. L. Robertson & J. A. Brown & T. McDonald & P. Jaksons, 2013. "BAS: Balanced Acceptance Sampling of Natural Resources," Biometrics, The International Biometric Society, vol. 69(3), pages 776-784, September.
    3. McIntyre, G.A., 2005. "A Method for Unbiased Selective Sampling, Using Ranked Sets," The American Statistician, American Statistical Association, vol. 59, pages 230-232, August.
    4. Omer Ozturk, 2017. "Statistical inference with empty strata in judgment post stratified samples," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(5), pages 1029-1057, October.
    5. Omer Ozturk & Olena Kravchuk, 2021. "Judgment Post-stratified Assessment Combining Ranking Information from Multiple Sources, with a Field Phenotyping Example," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 329-348, September.
    6. Anton Grafström & Lina Schelin, 2014. "How to Select Representative Samples," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 277-290, June.
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