JSM 2004 - Toronto

Abstract #302178

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Activity Number: 52
Type: Contributed
Date/Time: Sunday, August 8, 2004 : 4:00 PM to 5:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #302178
Title: Calibrated Imputation for the Drug Abuse Warning Network
Author(s): Andrea R. Piesse*+ and James L. Green
Companies: Westat and Westat
Address: , Rockville, MD, 20850,
Keywords:
Abstract:

This paper presents an imputation approach used for the Drug Abuse Warning Network (DAWN). DAWN uses a stratified, single-stage sample of hospitals to produce estimates for targeted DAWN areas and the nation. In some DAWN areas, data from one or more units are critical to the validity of the estimates for that area. These reporters are generally critical because they contain unusually large volumes of DAWN events or are otherwise atypical of other units in their area. Occasionally, data from a critical reporter becomes temporarily unavailable (i.e., periodic unit nonresponse). We have developed an improved imputation approach, outside of the standard survey imputation procedure, to deal with missing data for critical reporters. The approach uses time series models to obtain totals for important statistics in the missing data period, then uses linear programming to calibrate real reported data from an adjacent period to these modeled totals. The end result is a complete dataset.

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