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Improving State Capacity for Crime Reporting: an Exploratory Analysis of Data Quality and Imputation Methods Using NIBRS Data

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Improving State Capacity for Crime Reporting: an Exploratory Analysis of Data Quality and Imputation Methods Using NIBRS Data Criminal Justice Statistical Analysis Center January 2013 State of West Virginia Department of Military Affairs & Public Safety Division of Justice and Community Services Office of Research and Strategic Planning Improving State Capacity for Crime Reporting: An Exploratory Analysis of Data Quality and Imputation Methods Using NIBRS Data Christina R. LaValle, M.S., ORSP Research Analyst Stephen M. Haas, Ph.D., ORSP Director Erica Turley, B.S., ORSP Research Analyst James J. Nolan, Ph.D., West Virginia University Crime reporting in the United States originates Currently, elaborate methods established by from two major sources of data, the Uniform the Federal Bureau of Investigation (FBI) are used Crime Reports (UCR) and the National Incident- to evaluate UCR data quality in terms of outlier Based Reporting System (NIBRS). The incident- detection (see Akiyama & Propheter, 2005). The based reporting (IBR) structure of NIBRS is an FBI also imputes, or estimates, missing UCR data enhancement to the traditional summary reporting of using methods that were developed in 1958 (Maltz, UCR used to track crime in the U.S. While the law 1999). These methods are not timely, accurate, or enforcement community initiated IBR to address easy for state programs to administer since they the expanding complexity of crime, reporting often use data from regions involving multiple states crime using NIBRS, like UCR, is voluntary and rather than the individual state. Moreover, methods susceptible to issues of data quality, missing data, have not yet been applied to aggregate crime count and noncompliance. totals using NIBRS data and often reports using Data collected using UCR and NIBRS are used NIBRS data are criticized for being incomplete or for research and to document the status of crime at non-representative. the national, state, and county levels. Data quality With the intended replacement of UCR with regarding accuracy and completeness are critical to NIBRS, the need for data quality and imputation reliable results and information. Further, reporting methods in the context of NIBRS aggregate totals data “as is” without considering data quality and grows. By inspecting data quality and applying estimating for missing values may not be the most imputation methods to IBR data, this research accurate depiction of the process and can result in provides examples, recommendations, and easy-to- criticism. As funding and resources lessen, coupled use tools that can be employed by state repository with the multitude of data fields involved with IBR, personnel, researchers, and data analysts who issues of data quality and missingness are areas of analyze state-level IBR data. This study explored concern for analysts and researchers. In assessing data quality and handling missing data, appropriate and effective methods for resolving issues are necessary. data quality and imputation methods with the agencies report NIBRS data to the FBI which purpose of providing guidance to states reporting covers 27% of crime reported nationally and 29% IBR data and improving the utility of NIBRS data. of the population (Justice Research and Statistics Association [JRSA], 2012). Currently, 32 states Background are certified to report crime data to the FBI using The UCR and NIBRS data are both considered NIBRS; 13 of those states, including West Virginia3 primary sources of crime statistics (National report 100% of their crime using NIBRS (see Table Institute of Justice [NIJ], 2009). However, while 1) (JRSA, 2012). the UCR tracks crime offense totals for eight The NIBRS data, like the UCR, are not exempt crime categories (referred to as Index crimes), the from problems of data quality and missing values. NIBRS collects specific offense details of 22 crime The FBI checks UCR data monthly for anomalous categories (referred to as Group A crimes) (See reporting using several layers of control4. Data Appendix A for list of Summary UCR and NIBRS identified as outliers are flagged as missing and offense and arrest crime categories). Further, crime imputed. rates produced using UCR data consist of incident tallies where only the most serious crime is reported Table 1: Status of NIBRS data collection in the (known as the hierarchy rule), while crime rates United States using NIBRS data do not follow the hierarchy rule1. Thus, the UCR is referred to as a summary reporting Percent system where the NIBRS system involves incident- Coverage State based reporting since it collects several details for Less than Arizona, Louisiana, Missouri, each incident. 20% Oklahoma, Texas Data collected using an IBR system are 20% - 50% Maine, Nebraska, Oregon, particularly useful as they provide a wealth of Washington, Wisconsin information by gathering multiple attributes of each particular criminal incident in addition to 50% - 90% Colorado, Connecticut, Kansas, aggregating the data to provide summary crime Kentucky, Massachusetts, Ohio, counts. Thus, IBR data are used to investigate Utah complex criminological issues as well as provide 100% Arkansas, Delaware, Idaho, crime statistics and trends2. However, while the use Michigan, Montana, New of NIBRS data for research has gained in reception, Hampshire, Rhode Island, many studies are limited to specified populations South Carolina, South Dakota, since the data lack representative national coverage Tennessee, Vermont, Virginia, (Addington, 2008). West Virginia The conversion from UCR to NIBRS reporting Testing/ Alabama*, California, Illinois*, has been slow (James, 2008). In 2010, the UCR Developing Indiana, Maryland, Minnesota, covered 97.4 % of the total U.S. population and of Nevada, New Jersey, New that, NIBRS covered about 28% (Federal Bureau Mexico, New York, North of Investigation [FBI], 2011a, 2011b). NIBRS data Carolina, Pennsylvania, District received by the FBI are converted to UCR data of Columbia* before any data processing occurs for the annual No formal Alaska, Florida, Georgia, Crime in the U.S. report (L. Simmons, email, March plans Hawaii, Nevada, Wyoming 8, 2012). *NIBRS data from an individual agency is accepted by FBI As of June 2012, 43% of law enforcement Source: Status of NIBRS in States, 2012, JRSA 2 Improving State Capacity for Crime Reporting the current imputation methods used on the UCR Report Highlights... data were developed to produce annual national estimates of crime and are not appropriate for Reporting crime data “as is” without considering data smaller units of analysis (Lynch & Jarvis, 2008). quality and estimating for missing values can lead to The task of modernizing imputation methods has biased estimates of crime. been investigated by Michael Maltz and colleagues to not only better national estimates of crime, but This research hopes to improve state methods also provide estimates at smaller units of analysis. for estimating crime statistics through the use of In 2006, Maltz, Roberts, and Stasny compiled techniques that are accessible to state repository personnel, data analysts, and others who analyze state- a report for the American Statistical Association level IBR data. Committee on Law and Justice Statistics proposing improved imputation methods for crime data. Applying data quality and imputation methods are The report recommended different statistical pivotal to producing more accurate, stable, and reliable distribution-based imputation methods for different crime estimates. situations5. The report also suggested possible improvements for future work, including using the This research provides evidence that alternative average of months surrounding the missing month imputation methods improve the accuracy of crime and Bayesian methods. reporting for WV and may hold promise for other In 2011, Targonski suggested using longitudinal states. methods to impute for missing values in a final report to the Department of Justice. The proposed method suggested that for agencies missing ten to twelve months of data, a weight, calculated by The FBI’s method for imputing missing data dividing the current year’s group crime rate by the depends on the amount of data missing. For previous year’s group crime rate, was multiplied agencies missing one to nine months of data, the by the agency’s data reported in the prior year; for annual crime total is estimated by multiplying an agency missing one to nine months of data, a the total number of crimes for the year by twelve weight, calculated using the agency’s year-to-year then dividing by the number of months crime increase based on matched months reported, was were reported. For agencies missing ten to twelve multiplied by the agency’s previous year’s monthly months of data, the annual crime total is estimated data (see Targonski, 2011). by multiplying the agencies’ population by the Using suitable values to estimate missing data crime rate for the agencies’ population group are vital to filling in known gaps and bettering divided by 100,000 (Maltz, 1999). For agencies analyses and reporting. However, establishing that do not have an accompanying population such methods is a task of balance. Methods for “zero-population” agencies (e.g. State Police (SP), handling missing data have to be advanced enough Park Police, college campus security, etc.), data are to accurately estimate values yet accessible to be not imputed if not reported. employed with reasonable guidance. Though it may seem reasonable to apply FBI This research intended to develop and investigate data quality and imputation methods to NIBRS data, methods that would improve the accuracy of state it
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