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SURVWGT: Stata module to create and manipulate survey weights

Author

Listed:
  • Nick Winter

    (University of Virginia)

Programming Language

Stata

Abstract

survwgt creates sets of weights for replication-based variance estimation techniques for survey data. These include balanced repeated replication (BRR) and several version of the survey jackknife (JK*). These replication methods are alternates to the Taylor series linearization methods used by Stata's svy-based commands.

Suggested Citation

  • Nick Winter, 2002. "SURVWGT: Stata module to create and manipulate survey weights," Statistical Software Components S427503, Boston College Department of Economics, revised 11 Feb 2018.
    • Handle: RePEc:boc:bocode:s427503
    Note: This module may be installed from within Stata by typing "ssc install survwgt". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/s/survwgt.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/s/survwgt.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/b/brr_hadamardmatrixfile.ado
    File Function: program code
    Download Restriction: no
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    Citations

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    Cited by:

    1. Kris Wernstedt & Pamela Murray‐Tuite, 2015. "The Dynamic Nature of Risk Perceptions After a Fatal Transit Accident," Risk Analysis, John Wiley & Sons, vol. 35(3), pages 536-552, March.
    2. Kar H. Lim & Wuyang Hu, 2016. "How Local Is Local? A Reflection on Canadian Local Food Labeling Policy from Consumer Preference," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(1), pages 71-88, March.
    3. Bechlioulis, Alexandros P. & Karamanis, Dimitrios, 2020. "The impact of the Covid-19 lockdown on the i-banking use: An empirical inquiry from Greece," MPRA Paper 109392, University Library of Munich, Germany.
    4. Sonja Spitzer, 2020. "Biases in health expectancies due to educational differences in survey participation of older Europeans: It’s worth weighting for," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(4), pages 573-605, June.
    5. Lumley, Thomas, 2004. "Analysis of Complex Survey Samples," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i08).
    6. Cal J Halvorsen & Yu-Chih Chen, 2019. "The diversity of interest in later-life entrepreneurship: Results from a nationally representative survey of Americans aged 50 to 70," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-21, June.

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