Metadata record for Missing Data in the Uniform Crime Reports (UCR), 1977-2000 [United States] Inter-university Consortium for Political and Social Research ICPSR metadata records are licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License . 2013-05-22 Missing Data in the Uniform Crime Reports (UCR), 1977-2000 [United States] 32061 10.3886/ICPSR32061.v1 Targonski, Joseph United States Department of Justice. Office of Justice Programs. National Institute of Justice 2004-IJ-CX-0006 Inter-university Consortium for Political and Social Research 2012-11-26 Targonski, Joseph. Missing Data in the Uniform Crime Reports (UCR), 1977-2000 [United States]. ICPSR32061-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2012-11-26. doi:10.3886/ICPSR32061.v1 assault auto theft burglary crime rates crime reporting crime statistics larceny law enforcement murder offenses police police departments police records police reports rape records management robbery Uniform Crime Reports ICPSR.XVII.E NACJD.IX NACJD.VIII This study reexamined and recoded missing data in the Uniform Crime Reports (UCR) for the years 1977 to 2000 for all police agencies in the United States. The principal investigator conducted a data cleaning of 20,067 Originating Agency Identifiers (ORIs) contained within the Offenses-Known UCR data from 1977 to 2000. Data cleaning involved performing agency name checks and creating new numerical codes for different types of missing data including missing data codes that identify whether a record was aggregated to a particular month, whether no data were reported (true missing), if more than one index crime was missing, if a particular index crime (motor vehicle theft, larceny, burglary, assault, robbery, rape, murder) was missing, researcher assigned missing value codes according to the "rule of 20", outlier values, whether an ORI was covered by another agency, and whether an agency did not exist during a particular time period. The purpose of this study was to reexamine and recode missing data in the Uniform Crime Reports (UCR) for the years 1977 to 2000 for all police agencies in the United States.

The principal investigator performed a data cleaning of 20,067 Originating Agency Identifiers (ORIs) based on the Offenses-Known Uniform Crime Reporting (UCR) Program Data from 1977 to 2000. The UCR Offenses-Known data collection assembles monthly crime tabulations on what is known as the "Return A" form, which is submitted monthly by police agencies. This includes the crime index, which encompasses murder, rape, robbery, aggravated assault, burglary, larceny, and motor vehicle theft.

The agency-level files from 1977-2000 were merged by the principal investigator using the ORI as the key variable to create a single longitudinal dataset. The longitudinal dataset was further prepared and cleaned by the principal investigator to create the final version that is being distributed as part of this data collection. Data cleaning entailed performing agency name checks, identifying "true missing" values, creating monthly aggregation missing value codes, identifying agencies that are "covered by" another agency, flagging non-existent agencies, creating researcher assigned missing values according to the "rule of 20", and accounting for negative values as well as outlier values. Specifically, the principal investigator performed the following data cleaning tasks:

Agency name checks were performed to ensure the ORI code for each year refers to one and only one agency and to determine the years in which the ORI existed. Any month with a missing value for the Return A variable DATE LAST UPDATE was recoded as a "true missing" value (-99). To accurately account for the number of months reported, months that were flagged as missing by the DATE LAST UPDATE were recoded using distinct monthly aggregation missing value codes (-112 through -102). Some smaller agencies choose to report their UCR data through a larger neighboring agency, rather than report directly themselves to the FBI or state-reporting agency. This is a "covered by" situation, whereby the larger agency acts as the "covering" agency. For the analysis of missing data when an agency's data was "covered by" another agency, a missing value code (-85) was assigned to months in which the agency was covered by another agency. For the years that an ORI was not in existence between 1977 and 2000, another missing value code (-80) was also assigned to the months in which that particular agency did not exist. A missing value code (-90) was assigned according to a "rule of 20". The "rule of 20" established that an ORI with an average of 20 or more index crimes per month could not have zero index crimes in a month, if the DATE LAST UPDATE flagged the Return A as being submitted. For the purpose of screening outliers in the negative values, -4 was determined as the cutoff for legitimate values. Any values less than ?4 were recoded as missing values (-99), since they were most likely data entry errors. To identify additional outlier values, as part of the data screening process, each agency's trend was examined graphically. In the process, outliers were detected for the crime index. The outlier values were also recoded as -90. For the crimes of motor vehicle theft, larceny, burglary, assault, robbery, rape, and murder, missing data codes (-97 through -91) were assigned if a particular index crime was missing. Additionally, if more than one index crime was missing, it was assigned a separate missing data code (-98).

 This study contains a total of 410 variables including an Originating Agency Identifier (ORI) name and code, population totals by year, covering agency by year, statistical metropolitan area by year, county code by year, FBI group by year, and FBI crime index totals by month and year. 1977 2000 1977 2000 United States county agency All police agencies in the United States between 1977 and 2000. administrative records data The sample consists of 20,067 police agencies in the United States, as identified by all Originating Agency Identifiers (ORIs) in the Offenses-Known Uniform Crime Reporting data from 1977 to 2000. record abstracts UNIFORM CRIME REPORTING PROGRAM DATA: 1975-1997 [ICPSR 9028] UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 1998 [ICPSR 2904] UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 1999 [ICPSR 3158] UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2000 [ICPSR 3447] None.

ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

Created variable labels and/or value labels.Checked for undocumented or out-of-range codes. The principal investigator submitted data for this project in Microsoft Excel format. ICPSR is distributing the Microsoft Excel data so that secondary users can view the color codes developed by the principal investigator for the various forms of missing data. Additionally, ICPSR converted the original Microsoft Excel data into a full suite of formats for preservation and dissemination, including SAS, SPSS, and Stata formats. More detailed information about imputation methodologies in the Offenses-Known Uniform Crime Reports, data cleaning, and the creation and testing of simulation datasets is available in the project?s report (Targonski, 2011; NCJ 235152). Not applicable. None. Ann Arbor, Mi.: Inter-university Consortium for Political and Social Research Additional special permissions, where applicable, are described in the restrictions field.

Please read the terms of use below. If you agree to them, click on the "I Agree" button to proceed. If you do not agree, you can click on the "I Do Not Agree" button to return to the home page.

ICPSR adheres to the principles of the Data Seal of Approval , which, in part, require the data consumer to comply with access regulations imposed both by law and by the data repository, and to conform to codes of conduct that are generally accepted in higher education and scientific research for the exchange of knowledge and information.

These data are distributed under the following terms of use, which are governed by ICPSR. By continuing past this point to the data retrieval process, you signify your agreement to comply with the requirements stated below:

Privacy of RESEARCH SUBJECTS

Any intentional identification of a RESEARCH SUBJECT (whether an individual or an organization) or unauthorized disclosure of his or her confidential information violates the PROMISE OF CONFIDENTIALITY given to the providers of the information. Therefore, users of data agree:

To use these datasets solely for research or statistical purposes and not for investigation of specific RESEARCH SUBJECTS, except when identification is authorized in writing by ICPSR (netmail@icpsr.umich.edu )

To make no use of the identity of any RESEARCH SUBJECT discovered inadvertently, and to advise ICPSR of any such discovery (netmail@icpsr.umich.edu )

 Redistribution of Data

You agree not to redistribute data or other materials without the written agreement of ICPSR, unless:

You serve as the OFFICIAL or DESIGNATED REPRESENTATIVE at an ICPSR MEMBER INSTITUTION and are assisting AUTHORIZED USERS with obtaining data, or

You are collaborating with other AUTHORIZED USERS to analyze the data for research or instructional purposes.

When sharing data or other materials in these approved ways, you must include all accompanying files with the data, including terms of use. More information on permission to redistribute data can be found on the ICPSR Web site.

Citing Data

You agree to reference the recommended bibliographic citation in any publication that employs resources provided by ICPSR. Authors of publications based on ICPSR data are required to send citations of their published works to ICPSR for inclusion in a database of related publications (bibliography@icpsr.umich.edu ) .

Disclaimer

You acknowledge that the original collector of the data, ICPSR, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

Violations

If ICPSR determines that the terms of this agreement have been violated, ICPSR will act according to our policy on terms of use violations . Sanctions can include:

ICPSR may revoke the existing agreement, demand the return of the data in question, and deny all future access to ICPSR data.

The violation may be reported to the Research Integrity Officer, Institutional Review Board, or Human Subjects Review Committee of the user's institution. A range of sanctions are available to institutions including revocation of tenure and termination.

If the confidentiality of human subjects has been violated, the case may be reported to the Federal Office for Human Research Protections. This may result in an investigation of the user's institution, which can result in institution-wide sanctions including the suspension of all research grants.

A court may award the payment of damages to any individual(s)/organization(s) harmed by the breach of the agreement.

 Definitions authorized user - A faculty member, staff member, or student at a member institutionICPSR - Inter-university Consortium for Political and Social Researchmember institution - An institutional member of ICPSROfficial/Designated Representative - An individual appointed to represent a university's interests in ICPSR. This individual is also charged with providing user support to campus users. promise of confidentiality - A promise to a respondent or research participant that the information the respondent provides will not be disseminated without the permission of the respondent; that the fact that the respondent participated in the study will not be disclosed; and that disseminated information will include no linkages to the identity of the respondent. Such a promise encompasses traditional notions of both confidentiality and anonymity. Names and other identifying information regarding respondents, proxies, or other persons on whom the respondent or proxy provides information, are presumed to be confidential.research subject - A person or organization observed for purposes of research. Also called a respondent. A respondent is generally a survey respondent or informant, experimental or observational subject, focus group participant, or any other person providing information to a study or on whose behalf a proxy provides information.

In addition, the National Archive of Criminal Justice Data stipulates the following conditions:

Federal law and regulations require that research data collected by the U.S. Department of Justice or by its grantees and contractors may only be used for research or statistical purposes. The applicable laws and regulations may be found in the United States Code, 42 USC Section 3789g(a), the Code of Federal Regulations, 28 CFR 22, and 62 F.R. 35044 (June 27, 1997) (The Federal Confidentiality Order). Accordingly, any intentional identification or disclosure of a person or establishment may violate federal law as well as the assurances of confidentiality given to the providers of the information. Therefore, users of data collected by or with the support from the U.S. Department of Justice and distributed by NACJD or other ICPSR archives must agree to abide by these regulations and understand that ICPSR may report any potential violation to the U.S. Department of Justice.

AVAILABLE. This study is freely available to the general public.

 The original collector of the data, ICPSR, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.