Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. Law enforcement agencies contribute reports either directly or through their state reporting programs. Each year, summary data are reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Offenses Known and Clearances by Arrest data files include monthly data on the number of Crime Index offenses reported and the number of offenses cleared by arrest or other means. The counts include all reports of Index crimes (excluding arson) received from victims, officers who discovered infractions, or other sources. self-enumerated formsOffenses Known and Clearances by Arrest data for the years 1960-1974 have been released with a separate study number for each year. From 1975-1997 all UCR data can be found in UNIFORM CRIME REPORTING PROGRAM DATA: UNITED STATES. Starting with the year 1998, each of the four types of UCR summary data archived by ICPSR is released as a separate study under its own study number. Datasets: DS1: Uniform Crime Reporting Program Data [United States]: Offenses Known and Clearances by Arrest, 1966 Index crimes reported by law enforcement agencies in the United States. inap.

This indicator is based on location of residence. Mortality rate has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify homicides are X85-Y09, Y87.1, and U01-U02. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Violence is a public health crisis in the US, with gun violence being a major driver. Almost three quarters of homicides involve firearms. In the US, the age-adjusted homicide rate from firearms is more than 20 times higher than in the European Union or in Australia. Significant disparities by age, sex, and race and ethnicity exist, with young adults ages 15-34 years, males, and Black individuals most disproportionately impacted. Comprehensive prevention strategies should work to address the underlying physical, social, economic, and structural conditions known to increase risk.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

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. Datasets: DS0: Study-Level Files DS1: Incident-Level File DS2: Victim-Level File DS3: Offender-Level File DS4: Arrestee-Level File Law enforcement agencies in the United States participating in the National Incident-Based Reporting System. self-enumerated questionnaire

We develop a panel count model with a latent spatio-temporal heterogeneous state process for monthly severe crimes at the census-tract level in Pittsburgh, Pennsylvania. Our dataset combines Uniform Crime Reporting data with socio-economic data. The likelihood is estimated by efficient importance sampling techniques for high-dimensional spatial models. Estimation results confirm the broken-windows hypothesis whereby less severe crimes are leading indicators for severe crimes. In addition to ML parameter estimates, we compute several other statistics of interest for law enforcement such as spatio-temporal elasticities of severe crimes with respect to less severe crimes, out-of-sample forecasts, predictive distributions and validation test statistics.

Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as a periodic nationwide assessment of reported crimes not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Police Employee (LEOKA) Data provide information about law enforcement officers killed or assaulted (hence the acronym, LEOKA) in the line of duty. The variables created from the LEOKA forms provide in-depth information on the circumstances surrounding killings or assaults, including type of call answered, type of weapon used, and type of patrol the officers were on. self-enumerated questionnaireStarting with the year 1998, each of the four parts of the UCR data collection archived by ICPSR is released as a separate study under its own study number. The Police Employee data for the years 1975-1997 can be found in UNIFORM CRIME REPORTING PROGRAM DATA [UNITED STATES]: 1975-1997 (ICPSR 9028). Datasets: DS1: Uniform Crime Reporting Program Data [United States]: Police Employee (LEOKA) Data, 2004 Law enforcement officers killed or assaulted as reported by law enforcement agencies. inap.

Two major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than 3 months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting 0 months based on the procedures mentioned above. However, due to the structure of the data received from the FBI, estimations could not be produced for agencies reporting 0 months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting 1 or 2 months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.No arrest data were provided for Washington, DC, and Florida. Limited arrest data were available for Illinois and Kentucky. Limited offense data were available for Illinois, Kentucky, Mississippi, Missouri, Montana, and South Dakota.UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.Users should note that there are no records in the data for the borough of Denali, Alaska (FIPS code 02068) in any of the collections of the Uniform Crime Reporting Program Data [United States]: County-Level Detailed Arrest and Offense Data from 1990 to 2003. The borough of Denali, Alaska (FIPS code 02068) was created from part of the Yukon-Koyukuk Census Area (FIPS code 02290) an unpopulated part of the Southeast Fairbanks Census Area (FIPS code 02240) effective December 7, 1990. Since no agency records for either arrests or crimes reported from Denali were present in any of the original FBI files, no data for the borough of Denali, Alaska appear in any the ICPSR collections for these years. This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways). Datasets: DS0: Study-Level Files DS1: Arrests, All Ages DS2: Arrests, Adult DS3: Arrests, Juveniles DS4: Crimes Reported DS5: Allocated Statewide Data for Arrests, All Ages DS6: Allocated Statewide Data for Arrests, Adults DS7: Allocated Statewide Data for Arrests, Juveniles DS8: Allocated Statewide Data for Crimes Reported County law enforcement agencies in the United States.

This supplement to the National Crime Victimization Surveys (formerly the National Crime Surveys) was designed to collect data on crime victimization in schools in the United States. Student respondents were asked a series of questions to determine their school attendance in the last six months. Other questions concerning schools were posed, including type of school, distance from home, and general attendance and monitoring policies. The data present information on the response of the school to student violation of rules, accessibility of drugs, and violence in school, including types of violence and student reaction. Other variables cover general violent crimes, personal larceny crimes, and household crimes and offer information on date, time, and place of crime. Demographic characteristics of household members such as age, sex, race, education, employment, median family income, and marital status are provided. The codebook and data collection instrument are provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet. Stratified multistage cluster sample of households with children between the ages of 12-19, who had attended school at any time during the six months prior to the month of the interview, and who were enrolled in a school that would advance them toward the eventual receipt of a high school diploma. Datasets: DS1: National Crime Victimization Survey: School Crime Supplement, 1995 All persons in the United States 12 years of age and older.

Mortality rate from firearms includes homicides, suicides, accidental deaths, deaths by law enforcement, and deaths for which intent was undetermined. Mortality rate is based on the location of residence and has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify firearm deaths are W32-W34, X72-X74, X93-X95, Y22-Y24, Y35.0, and U01.4. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Violence is a public health crisis in the US, with gun violence being a major driver. In the US, the age-adjusted homicide rate from firearms is more than 20 times higher than in the European Union or in Australia. Significant disparities by age, sex, and race and ethnicity exist, with young adults (ages 15-34 years), males, and Black individuals most disproportionately impacted. Firearm-related suicides disproportionately impact older, White men. Comprehensive prevention strategies should work to address underlying physical, social, economic, and structural conditions known to increase risk.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This data collection tabulates the number of persons convicted of felonies in state courts and describes the sentences these individuals received. Data were collected from state courts and state prosecutors in 100 counties of the United States. Sociodemographic information includes age, race, and sex of felon. Types of offenses committed include homicide, rape, and robbery. Adjudication variables referring to the process between arrest and sentencing are also a part of this dataset. Data can be analyzed on a national level or by the individual counties. A two-stage stratified cluster sampling design was employed. At the first stage all counties in the nation were divided into six strata. At the second stage, a systematic sample of felons sentenced for murder/nonnegligent manslaughter, rape, robbery, aggravated assault, burglary, felony larceny/motor vehicle theft, drug trafficking, and other offenses was selected from each county's official records. Datasets: DS1: National Judicial Reporting Program, 1986 Sentenced felons in the United States.