FARS2024NationalSAS.zip

File Identity

FARS2024NationalSAS.zip is the 2024 national SAS dataset package for NHTSA's Fatality Analysis Reporting System. FARS is a census of fatal motor vehicle traffic crashes in the United States. The national SAS package contains the same crash records, person records, vehicle records, and factor-level tables as FARS2024NationalCSV.zip, but delivered as SAS7BDAT binary datasets rather than plain-text CSV files.^1,2,3

What SAS7BDAT Format Means

SAS7BDAT is the native binary dataset format for SAS statistical software. Unlike a CSV, a SAS7BDAT file stores not only the data values but also embedded variable names, variable labels, and references to value format definitions. This means a SAS user can run a PROC CONTENTS or PROC PRINT on the FARS datasets and see descriptive labels for each field rather than raw numeric codes.^3,4

Value format definitions are stored in the separate formats.sas7bcat catalog file included in the package. To see decoded labels rather than raw codes in SAS output, the catalog must be added to the FMTSEARCHsystem option before running any procedures. Researchers working outside of SAS can read SAS7BDAT files using open-source libraries such as R's haven package or Python's pyreadstat package, though format catalog application may vary by tool.⁴

What the Package Contains

The ZIP contains SAS7BDAT datasets covering crash-level, person-level, vehicle-level, and factor-level records, plus a SAS formats catalog. The core tables used for most summary statistics are accident.sas7bdat for crash records and person.sas7bdat for fatality details. The formats catalog must be loaded alongside the datasets to decode numeric coded values.^3,4

The complete SAS package mirrors the table structure of the national CSV release. Consult the FARS analytical reference guide for a full description of every table and variable included in the 2024 release.⁴

SAS Package vs. CSV Package

Both FARS2024NationalSAS.zip and FARS2024NationalCSV.zip contain the same underlying 2024 fatal crash records. The choice between them depends on the analysis environment, not on data coverage or content.^2,3,5

The CSV package is generally easier to inspect in a text editor, import into spreadsheet software, or process with general-purpose scripting tools. The SAS package is preferred when working in SAS software because the SAS7BDAT format preserves embedded variable labels and format references, reducing the need to manually apply a separate coding manual during analysis. Researchers who use R or Python can read either format, though most pipelines in those languages start with the CSV package.^4,5

How Daily Driver Advocate Uses It

Daily Driver Advocate publishes derived summaries built from the CSV package rather than the SAS package, since the site's TypeScript data pipeline reads plain-text CSV files. This source card documents FARS2024NationalSAS.zip as a companion reference for researchers who work in SAS or who need to cite the complete set of official NHTSA 2024 FARS national packages.^1,3,5

Common Research Uses

This package is most useful for researchers and government analysts who work in SAS and want to access 2024 national fatal crash data directly in their existing SAS environment without a format-conversion step.^1,3,4

Important Limitations

• FARS covers fatal crashes only. It is not a count of all crashes, injury-only crashes, property-damage claims, or insurance losses.
• A crash must involve a motor vehicle on a public trafficway and result in a death within 30 days to be included.
• The SAS7BDAT format is a proprietary binary format. Reading the files outside of SAS requires a compatible library such as R's haven package or Python's pyreadstat package.
• The data content is identical to FARS2024NationalCSV.zip. The two packages differ only in file format; researchers should choose the format that matches their analysis environment.
• The formats catalog (formats.sas7bcat) must be loaded in the SAS FMTSEARCH path before SAS procedures will display decoded value labels rather than raw numeric codes.
• State totals must be derived from the STATE field in accident.sas7bdat. The national SAS package is not pre-aggregated by state.
• Population-adjusted rates require a separate denominator source such as Census Vintage 2024 state population estimates.

Suggested Citation

For the raw dataset, cite NHTSA as the issuing agency and link to the official file. For this explanatory card, cite Daily Driver Advocate as the independent research project that documented the source.