DOI: 10.3886/e102180v12-139017
title: Jacob Kaplan's Concatenated Files: Uniform Crime Reporting Program Data: Law Enforcement Officers Killed and Assaulted (LEOKA) 1960-2021

description: <b><b>For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.com</b></b><b><br></b><b>Version 12 release notes:<br></b><b></b>Adds 2021 data.<br><b>Version 11 release notes:<br></b>Adds 2020 data. <br>Please note that the FBI has retired UCR data ending in 2020 data so this will (probably, I haven't seen confirmation either way) be the last LEOKA data they release. <br>Changes .rda file to .rds.<b>Version 10 release notes:</b>Changes release notes description, does not change data.<b>Version 9 release notes:</b><b></b>Adds data for 2019.<br><b>Version 8 release notes:</b>Fix bug for years 1960-1971 where the number of months reported variable was incorrectly down by 1 month. I recommend caution when using these years as they only report either 0 or 12 months of the year, which differs from every other year in the data. <br>Added the variable officers_killed_total which is the sum of officers_killed_by_felony and officers_killed_by_accident.<br><b>Version 7 release notes:</b>Adds data from 2018<br><b>Version 6 release notes:</b><br>Adds data in the following formats: SPSS and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.<br><b></b><b>Version 5 release notes: <br></b>Adds data for 1960-1974 and 2017.<b> Note: many columns (including number of female officers) will always have a value of 0 for years prior to 1971. This is because those variables weren't collected prior to 1971. These should be NA, not 0 but I'm keeping it as 0 to be consistent with the raw data. <br></b>Removes support for .csv and .sav files.Adds a number_of_months_reported variable for each agency-year. A month is considered reported if the month_indicator column for that month has a value of "normal update" or "reported, not data."<b>The formatting of the monthly data has changed from wide to long. This means that each agency-month has a single row. The old data had each agency being a single row with each month-category (e.g. jan_officers_killed_by_felony) being a column. Now there will just be a single column for each category (e.g. </b><b>officers_killed_by_felony</b><b>) and the month can be identified in the month column. This also results in most column names changing. <br></b>As such, be careful when aggregating the monthly data since some variables are the same every month (e.g. number of officers employed is measured annually)<b> </b>so aggregating will be 12 times as high as the real value for those variables. <b><br></b><b>Adds a date column. This date column is always set to the first of the month. It is NOT the date that a crime occurred or was reported. It is only there to make it easier to create time-series graphs that require a date input.</b>All the data in this version was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. Data is the same as from NACJD but using all FBI files makes cleaning easier as all column names are already identical. <b><br></b><b>Version 4 release notes: </b><br>Add data for 2016.Order rows by year (descending) and ORI.<b>Version 3 release notes: <b><br></b></b>Fix bug where Philadelphia Police Department had incorrect FIPS county code. <br>The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. <br><br>All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. <br><br>About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself. <br><br>Several agency had impossible large (&gt;15) officer deaths in a single month. For those months I changed the value to NA. <br><br>The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:<br><br>"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety.<br><br>"... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."<br><br>
description: Law enforcement agencies in the United States.<br>. Smallest Geographic Unit: Police agency jurisdiction