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Activity Number: 13
Type: Topic Contributed
Date/Time: Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #310418
Title: Imputing Missing Data in the FBI's Uniform Crime Reports
Author(s): Clint Roberts*+ and Elizabeth A. Stasny and Michael D. Maltz
Companies: The Ohio State University and The Ohio State University and The Ohio State University
Address: 2513 Mt. Holyoke Rd., Columbus, OH, 43221,
Keywords: GLM ; Poisson regression ; Time series
Abstract:

The Uniform Crime Reports, collected by the FBI, contain monthly crime counts for each of the seven index crimes, but for one reason or another, a police agency may miss reporting for a particular month. The data are not complete, hence the need for the development of an imputation procedure to fill in the gaps. Since the early 1960's, an imputation technique implemented by the FBI has been used to make annual crime count estimates. This approach ignores concerns of seasonality and does not make use of the agencies' long-term data trends. Computing power has radically improved since the 1960's, and it is now feasible to develop a more involved yet flexible method that can incorporate more information into our estimation procedure. Our model-based approach also has the added value of making available variance estimates for the imputed data.

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Revised September, 2007