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The Theory and Practice of Maximal Brewer Selection with Poisson PRN Sampling

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  • Kott, Phillip S.
  • Bailey, Jeffrey T.

Abstract

K.R.W. Brewer suggests that when estimating the total of a single item for which there is control (auxiliary) data, one employ a ratio or regression estimator and draw the sample using probabilities proportional to the control values raised to a power between 1/2 and 1. Brewer's sample selection scheme can be expanded to multiple targets by drawing overlapping Poisson samples for a number of items simultaneously using permanent random numbers (PRN's). W e can call the result an example of "Maximal Brewer Selection" (MBS). This paper develops the theory behind MBS and the calibration estimator rendering it practical. It goes on to describe ho w this estimation strategy is being used at the National Agricultural Statistics Service.

Suggested Citation

  • Kott, Phillip S. & Bailey, Jeffrey T., 2000. "The Theory and Practice of Maximal Brewer Selection with Poisson PRN Sampling," NASS Research Reports 234380, United States Department of Agriculture, National Agricultural Statistics Service.
    • Handle: RePEc:ags:unasrr:234380
    DOI: 10.22004/ag.econ.234380
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    References listed on IDEAS

    as
    1. Kott, Phillip S. & Fetter, Matthew J., 1999. "Using Multi-Phase Sampling to Limit Respondent Burden Across Agriculture Surveys," NASS Research Reports 235075, United States Department of Agriculture, National Agricultural Statistics Service.
    2. List, John A, et al, 2001. "Academic Economists Behaving Badly? A Survey on Three Areas of Unethical Behavior," Economic Inquiry, Western Economic Association International, vol. 39(1), pages 162-170, January.
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    Cited by:

    1. Lisic Jonathan & Sang Hejian & Zhu Zhengyuan & Zimmer Stephanie, 2018. "Optimal Stratification and Allocation for the June Agricultural Survey," Journal of Official Statistics, Paradigm, vol. 34(1), pages 121-148, March.
    2. repec:ags:unassr:235089 is not listed on IDEAS
    3. R. Benedetti & M. S. Andreano & F. Piersimoni, 2019. "Sample selection when a multivariate set of size measures is available," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 1-25, March.
    4. Kott, Phillip S., 2001. "Using the Delete-a-Group Jackknife Variance Estimator in NASS Surveys," NASS Research Reports 235089, United States Department of Agriculture, National Agricultural Statistics Service.
    5. Linda J. Young & Lu Chen, 2022. "Using Small Area Estimation to Produce Official Statistics," Stats, MDPI, vol. 5(3), pages 1-17, September.

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