IDEAS home Printed from https://ideas.repec.org/p/ags/unasrr/235089.html
   My bibliography  Save this paper

Using the Delete-a-Group Jackknife Variance Estimator in NASS Surveys

Author

Listed:
  • Kott, Phillip S.

Abstract

The National Agricultural Statistics Service (NASS) plans to use estimation strategies of increasing complexity in the future and will need to estimate the variances resulting from those strategies. This report describes a relatively simple method of variance/mean squared error estimation, the delete-agroup jackknife, that can be used meaningfully in a remarkably broad range of settings employing complex estimation strategies. The text describes a number of applications of the method in abstract terms. It goes on to shows how the delete-a-group jackknife has been applied to some recent NASS surveys.

Suggested Citation

  • 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.
    • Handle: RePEc:ags:unasrr:235089
    DOI: 10.22004/ag.econ.235089
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/235089/files/Using_the_Delete-a-Group_Jackknife_Estimator_in_NASS_Surveys.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.235089?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Kott, Phillip S., 1997. "A (Partially) Model-Based Look at Jackknife Variance Estimation with Two-Phase Samples," NASS Research Reports 234300, United States Department of Agriculture, National Agricultural Statistics Service.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luca Sartore & Kelly Toppin & Linda Young & Clifford Spiegelman, 2019. "Developing Integer Calibration Weights for Census of Agriculture," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 26-48, March.
    2. Paolo Righi & Stefano Falorsi & Andrea Fasulo, 2014. "Methods for variance estimation under random hot deck imputation in business surveys," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 16(1-2), pages 45-64.
    3. Kleiber, Kandice, 2009. "The Effect of Ethanol-Driven Corn Demand on Crop Choice," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49616, Agricultural and Applied Economics Association.
    4. Lambert, Dayton M. & Schaible, Glenn D. & Johansson, Robert C. & Daberkow, Stan G., 2006. "Working-Land Conservation Structures: Evidence on Program and Non-Program Participants," 2006 Annual meeting, July 23-26, Long Beach, CA 21438, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. An, Henry, 2012. "Complementarities in Production Technologies: An Empirical Analysis of the Dairy Industry," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124653, Agricultural and Applied Economics Association.
    6. Dong, Fengxia & Mitchell, Paul D., 2023. "Economic and risk analysis of sustainable practice adoption among U.S. corn growers," Agricultural Systems, Elsevier, vol. 211(C).
    7. Lu Chen & Luca Sartore & Habtamu Benecha & Valbona Bejleri & Balgobin Nandram, 2022. "Smoothing County-Level Sampling Variances to Improve Small Area Models’ Outputs," Stats, MDPI, vol. 5(3), pages 1-18, September.
    8. Musser, Wesley N. & Lambert, Dayton M. & Daberkow, Stan G., 2006. "Factors Affecting Direct and Indirect Energy Use in U.S. Corn Production," 2006 Annual meeting, July 23-26, Long Beach, CA 21063, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Parcel Joshua D. & Schroeter John R. & Azzam Azzeddine M, 2017. "A Re-Examination of Multistage Economies in Hog Farming," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 15(2), pages 1-15, December.
    10. Kott, Phillip S. & Garren, Steven T., 2009. "Evaluating the Asymptotic Limits of the Delete-a-Group Jackknife for Model Analyses," NASS Research Reports 234370, United States Department of Agriculture, National Agricultural Statistics Service.
    11. McCarthy Jaki & Wagner James & Sanders Herschel Lisette, 2017. "The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design," Journal of Official Statistics, Sciendo, vol. 33(3), pages 857-871, September.
    12. Lambert, Dayton M. & Sullivan, Patrick, 2006. "Conservation Reserve Program Participation and Acreage Enrollment of Working Farms," 2006 Annual meeting, July 23-26, Long Beach, CA 21361, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. repec:ags:unassr:234370 is not listed on IDEAS
    14. Eilya Torshizian & Arthur Grimes, 2021. "Household Crowding Measures: A Comparison and External Test of Validity," Journal of Happiness Studies, Springer, vol. 22(4), pages 1925-1951, April.
    15. An, Henry, 2008. "The Adoption and Disadoption of Recombinant Bovine Somatotropin in the U.S. Dairy Industry," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6278, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:ags:unassr:235089 is not listed on IDEAS
    2. Linda J. Young & Lu Chen, 2022. "Using Small Area Estimation to Produce Official Statistics," Stats, MDPI, vol. 5(3), pages 1-17, September.
    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. Lisic Jonathan & Sang Hejian & Zhu Zhengyuan & Zimmer Stephanie, 2018. "Optimal Stratification and Allocation for the June Agricultural Survey," Journal of Official Statistics, Sciendo, vol. 34(1), pages 121-148, March.

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:unasrr:235089. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://www.nass.usda.gov/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.