National Incident-Based Reporting System, 2010: Extract Files (ICPSR 33601)

Version Date: Jun 27, 2012 View help for published

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National Archive of Criminal Justice Data

Series:

https://doi.org/10.3886/ICPSR33601.v1

Version V1 ()

  • V2 [2018-10-01]
  • V1 [2012-06-27] unpublished

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Additional information about this collection can be found in Version History.

2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:

  • National Archive of Criminal Justice Data. National Incident-Based Reporting System, 2010: Extract Files. ICPSR33601-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2012-06-27. http://doi.org/10.3886/ICPSR33601.v1

2012-06-27 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.
  • Standardized missing values.
  • Performed recodes and/or calculated derived variables.
  • Checked for undocumented or out-of-range codes.

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NIBRS, 2010

The National Incident-Based Reporting System (NIBRS) is a part of the Uniform Crime Reporting Program (UCR), administered by the Federal Bureau of Investigation (FBI). The extract files version of NIBRS was created to simplify working with NIBRS data. Data management issues with NIBRS are significant, especially when two or more segment levels are being merged. These issues require skills separate from data analysis. NIBRS data as formatted by the FBI are stored in a single file. These data are organized by various segment levels (record types). There are six main segment levels: administrative, offense, property, victim, offender, and arrestee. Each segment level has a different length and layout. There are other segment levels that occur with less frequency than the six main levels. Significant computing resources are necessary to work with the data in its single-file format. In addition, the user must be sophisticated in working with data in complex file types. For these reasons and the desire to facilitate the use of NIBRS data, ICPSR created the extract files. The data are not a representative sample of crime in the United States.

National Archive of Criminal Justice Data. National Incident-Based Reporting System, 2010: Extract Files. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2012-06-27. https://doi.org/10.3886/ICPSR33601.v1

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United States Department of Justice. Office of Justice Programs. Federal Bureau of Investigation, United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics

city

Inter-university Consortium for Political and Social Research
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2010
2010
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Cross-sectional

Law enforcement agencies in the United States participating in the National Incident-Based Reporting System.

Dataset four - Arrestee, Dataset one - Incident, Dataset three - Offender, Dataset two - Victim
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2012-06-27

2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:
  • National Archive of Criminal Justice Data. National Incident-Based Reporting System, 2010: Extract Files. ICPSR33601-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2012-06-27. http://doi.org/10.3886/ICPSR33601.v1

2012-06-27 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.
  • Standardized missing values.
  • Performed recodes and/or calculated derived variables.
  • Checked for undocumented or out-of-range codes.
Hide