Abstract #300333

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JSM 2003 Abstract #300333
Activity Number: 58
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Social Statistics Section
Abstract - #300333
Title: Cleaning and Imputing FBI-Collected Crime Data, 1997-2000
Author(s): Michael D. Maltz*+
Companies: University of Illinois, Chicago
Address: 1007 W Harrison St., Chicago, IL, 60607-7135,
Keywords: crime data ; missingness ; imputation ; FBI ; Uniform Crime Reports
Abstract:

Monthly crime data from over 18,000 police agencies are compiled by the FBI's Uniform Crime Reporting (UCR) Program. The data are submitted voluntarily to the UCR Program, so the FBI has to deal with missing data and imputes to fill in gaps. Missing data may be reported as missing (empty cell) or as a 0 or as a 999; the data may then be recorded as missing, or 0 or 999 crimes. Missing data may be aggregated and reported in a subsequent month. Data may be missing-at-random due to agency problems, or not reported because the agency has little or no crime. No imputation is done for nonprimary agencies in a jurisdiction (e.g., campus or transit police) that may have reporting gaps. Agency data may be double-counted, i.e., directly and through other agencies (e.g., agencies that are "covered by" sheriff's departments). We have developed missingness-based techniques to clean the 1977-2000 UCR data. We use graphical methods, as there may be idiosyncratic problems that refer to some agencies and not others. We describe the methods used to track and repair the data anomalies and the imputation strategy we intend to use.

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