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

Kott Phillip S. () and Day C. Daniel ()
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Kott Phillip S.: RTI International, 6110 Executive Blvd., Rockville, MD 20852, U.S.A
Day C. Daniel: Substance Abuse and Mental Health Services Administration, 1 Choke Cherry Road, Rockville MD 20857, U.S.A

Journal of Official Statistics, 2014, vol. 30, issue 3, 521-532

Abstract: 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 (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:30:y:2014:i:3:p:12:n:11

DOI: 10.2478/jos-2014-0032

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