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Logistic Propensity Models to Adjust for Nonresponse in Physician Surveys

Author

Listed:
  • Nuria Diaz-Tena
  • Frank Potter
  • Michael Sinclair
  • Stephen Williams

Abstract

Looks at the advantages of using a different number of weighting cells or propensity scores to adjust for nonresponse in the Community Tracking Study physician survey.

Suggested Citation

  • Nuria Diaz-Tena & Frank Potter & Michael Sinclair & Stephen Williams, "undated". "Logistic Propensity Models to Adjust for Nonresponse in Physician Surveys," Mathematica Policy Research Reports 9b05a530def14b9694a5a27e0, Mathematica Policy Research.
  • Handle: RePEc:mpr:mprres:9b05a530def14b9694a5a27e039fbf94
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    File URL: https://www.mathematica-mpr.com/-/media/publications/pdfs/logisticpropen.pdf
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    More about this item

    Keywords

    Nonresponse weighting ; Propensity Modeling ; Weighting Classes ; Community Trackiing Study ; Physician Surveys;

    JEL classification:

    • I - Health, Education, and Welfare

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