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Journal of Official Statistics

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Developing Calibration Weights and Standard-Error Estimates for a Survey of Drug-Related Emergency-Department Visits

Phillip S. Kott / C. Daniel Day
Published Online: 2014-09-02 | DOI: https://doi.org/10.2478/jos-2014-0032


This article describes a two-step calibration-weighting scheme for a stratified simple random sample of hospital emergency departments. The first step adjusts for unit nonresponse. The second increases the statistical efficiency of most estimators of interest. Both use a measure of emergency-department size and other useful auxiliary variables contained in the sampling frame. Although many survey variables are roughly a linear function of the measure of size, response is better modeled as a function of the log of that measure. Consequently the log of size is a calibration variable in the nonresponse-adjustment step, while the measure of size itself is a calibration variable in the second calibration step. Nonlinear calibration procedures are employed in both steps. We show with 2010 DAWN data that estimating variances as if a one-step calibration weighting routine had been used when there were in fact two steps can, after appropriately adjusting the finite-population correct in some sense, produce standard-error estimates that tend to be slightly conservative.

Keywords: Frame variable; response model; prediction model; general exponential model; finite population correction


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About the article

Received: 2012-11-01

Revised: 2014-02-01

Accepted: 2014-05-01

Published Online: 2014-09-02

Published in Print: 2014-09-01

Citation Information: Journal of Official Statistics, Volume 30, Issue 3, Pages 521–532, ISSN (Online) 2001-7367, DOI: https://doi.org/10.2478/jos-2014-0032.

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© by Phillip S. Kott. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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