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

• Main Authors: Kott Phillip S., Day C. Daniel
• Format: Article
• Language: English
• Published: Sciendo 2014-09-01
• Series: Journal of Official Statistics
• Subjects: frame variable; response model; prediction model; general exponential model; finite population correction
• Online Access: 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.