Searchable Codebooks"
In rfars: Download and Analyze Crash Data

library(rfars)
library(dplyr)
library(stringr)

rfars comes pre-loaded with searchable codebooks, compiled from SAS format files and the User Manuals (see: FARS Analytical User's Manual and CRSS Analytical User's Manual).

Access the codebooks in RStudio with:

View(rfars::fars_codebook)
View(rfars::gescrss_codebook)

It can be helpful to search the codebooks for certain concepts. The examples below illustrate the content of the codebooks and how variables change over time.

Here we search for the word alcohol in any of the codebook fields, including the names of tables, various versions of variable names, the definition, all value labels, and additional information from the User Manual if present.

cb <- rfars::fars_codebook %>% filter(if_any(everything(), ~ str_detect(., "alcohol"))) 

distinct(cb, source, file, name_ncsa, name_rfars, label, Definition, `Additional Information`) %>%
  knitr::kable(format = "html")

The drinking variable changed in a very minor way:

filter(cb, name_rfars == "drinking") %>%
  distinct(name_rfars, value_label, `2014`, `2015`, `2016`, `2017`, `2018`, `2019`, `2020`, `2021`, `2022`, `2023`) %>%
  knitr::kable(format = "html")

But the variable for driver distraction changed names in 2020:

filter(cb, name_rfars %in% c("mdrdstrd", "drdistract")) %>%
  distinct(name_rfars, value_label, `2014`, `2015`, `2016`, `2017`, `2018`, `2019`, `2020`, `2021`, `2022`, `2023`) %>%
  arrange(value_label, name_rfars) %>%
  knitr::kable(format = "html")

As another example, the per_typ variable has undergone more substantial changes over time.

filter(rfars::fars_codebook, name_rfars == "per_typ") %>%
  distinct(name_rfars, value_label, `2014`, `2015`, `2016`, `2017`, `2018`, `2019`, `2020`, `2021`, `2022`, `2023`) %>%
  arrange(value_label, name_rfars) %>%
  knitr::kable(format = "html")