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## Attaching package: 'dplyr'
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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:

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")
source file name_ncsa name_rfars label Definition Additional Information
FARS vehicle DR_DRINK dr_drink Driver Drinking This data element records whether the driver was drinking. This data element is derived from data elements in the Vehicle and Person data files. Data are analyzed and if there is "sufficient information" to conclude that a driver was drinking, i.e., positive BAC data or police-reported alcohol involvement, then a driver is classified as drinking. A driver is classified as drinking (alcohol-involved) if the driver has (1) police-reported alcohol involvement, or (2) a positive alcohol test result. A driver who is charged with an alcohol violation does not by itself make the driver a "drinking driver" by this definition. Note that alcohol data is often missing. For that reason, this data element may under-count the actual number of drinking drivers.
FARS person DRINKING drinking Police Reported Alcohol Involvement This data element records whether alcohol was involved for this person and reflects the judgment of law enforcement. This data element does not indicate that alcohol was a cause of the crash. If a police crash report indicates that opened or unopened alcohol bottles were found in the vehicle, then this information does not by itself constitute involvement. Prior to 2019 the Data Element ID was P16/NM15. From 2019-2021 the Element Data ID was P16/NM16.
FARS person ALC_STATUS alc_status Alcohol Test- Status This data element identifies whether an alcohol test was given to this person. Prior to 2019 the Data Element ID was P18A/NM17A. From 2019-2021 the Data Element ID was P18A/NM18A.
FARS person ATST_TYP atst_typ Alcohol Test- Type This data element identifies the type of alcohol test that was given to this person. Prior to 2019 the Data Element ID was P18B/NM17B. From 2019-2021 the Data Element ID was P18B/NM18B.
FARS person ALC_RES alc_res Alcohol Test- Result This data element identifies the alcohol test result for this person. NA
FARS distract MDRDSTRD mdrdstrd Driver Distracted By NA Distraction from the primary task of driving occurs when drivers divert their attention from the driving task to some other activity. Also, driving while daydreaming or lost in thought is identified as distracted driving by NHTSA. Physical conditions/impairments (fatigue, alcohol, medical condition, etc.) or psychological states (anger, emotional, depressed, etc.) are not identified as distractions by NHTSA. Although the attribute 1 (Looked but Did Not See) was included in this element, this attribute is not considered a distraction and therefore should not be included in any distraction analysis.
FARS violatn MVIOLATN mviolatn Violations Charged This data element documents the violations, citations, or infractions of the Vehicle Code issued on the police crash report for this driver in this crash, regardless of whether the driver survived the crash. Prior to 2010 this data element was in the Vehicle data file. In 2010 this data element changed to identify all violations charged in the crash and was therefore moved here to its own data file.
FARS vehicle PREV_SUS1 prev_sus1 Previous Underage Administrative Per Se for BAC This data element records any underage pre-conviction administrative license suspension, revocation, or withdrawal in the 5 years prior to the crash date including those for zero-tolerance alcohol violations while driving or refusing to submit to chemical testing. This element is only for administrative actions associated with alcohol. These are NOT BAC convictions. Prior to 2015 the time frame for this data element was any occurrence within 3 years of the crash date.
FARS vehicle PREV_SUS2 prev_sus2 Previous Administrative Per Se for BAC (Not Underage) This data element records the count of previous pre-conviction administratively imposed suspensions, revocations, or withdrawals within the 5 years prior to the crash date for driving with a BAC above a specified limit or refusing to submit to chemical testing. This element is only for administrative actions associated with alcohol. These are NOT BAC convictions. Prior to 2015 the time frame for this data element was any occurrence within 3 years of the crash date.
FARS distract DRDISTRACT drdistract Driver Distracted By NA Distraction from the primary task of driving occurs when drivers divert their attention from the driving task to some other activity. Also, driving while daydreaming or lost in thought is identified as distracted driving by NHTSA. Physical conditions/impairments (fatigue, alcohol, medical condition, etc.) or psychological states (anger, emotional, depressed, etc.) are not identified as distractions by NHTSA. Although the attribute 1 (Looked but Did Not See) was included in this element, this attribute is not considered a distraction and therefore should not be included in any distraction analysis.
FARS violatn VIOLATION violation Violations Charged This data element documents the violations, citations, or infractions of the Vehicle Code issued on the police crash report for this driver in this crash, regardless of whether the driver survived the crash. Prior to 2010 this data element was in the Vehicle data file. In 2010 this data element changed to identify all violations charged in the crash and was therefore moved here to its own data file.

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")
name_rfars value_label 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
drinking No (Alcohol Not Involved) 1 1 1 1 1 1 1 1 1 1
drinking Yes (Alcohol Involved) 1 1 1 1 1 1 1 1 1 1
drinking Not Reported 1 1 1 1 1 1 1 1 1 1
drinking Unknown (Police Reported) 1 1 1 1 NA NA NA NA NA NA
drinking Reported as Unknown NA NA NA NA 1 1 1 1 1 1

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")
name_rfars value_label 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
drdistract Adjusting Audio Or Climate Controls NA NA NA NA NA NA 1 1 1 1
mdrdstrd Adjusting Audio Or Climate Controls 1 1 1 1 1 1 NA NA NA NA
drdistract By a Moving Object in Vehicle NA NA NA NA NA NA 1 1 1 1
mdrdstrd By a Moving Object in Vehicle 1 1 1 1 1 1 NA NA NA NA
drdistract By Other Occupant(s) NA NA NA NA NA NA 1 1 1 1
mdrdstrd By Other Occupant(s) 1 1 1 1 1 1 NA NA NA NA
drdistract Careless/Inattentive NA NA NA NA NA NA 1 1 1 1
mdrdstrd Careless/Inattentive 1 1 1 1 1 1 NA NA NA NA
drdistract Distracted by Outside Person, Object or Event NA NA NA NA NA NA 1 1 1 1
mdrdstrd Distracted by Outside Person, Object or Event 1 1 1 1 1 1 NA NA NA NA
drdistract Distraction (Distracted), Details Unknown NA NA NA NA NA NA 1 1 1 1
mdrdstrd Distraction (Distracted), Details Unknown 1 1 1 1 1 1 NA NA NA NA
drdistract Distraction/Careless NA NA NA NA NA NA 1 1 1 1
mdrdstrd Distraction/Careless 1 1 1 1 1 1 NA NA NA NA
drdistract Distraction/Inattention NA NA NA NA NA NA 1 1 1 1
mdrdstrd Distraction/Inattention 1 1 1 1 1 1 NA NA NA NA
drdistract Eating or Drinking NA NA NA NA NA NA 1 1 1 1
mdrdstrd Eating or Drinking 1 1 1 1 1 1 NA NA NA NA
drdistract Inattention (Inattentive), Details Unknown NA NA NA NA NA NA 1 1 1 1
mdrdstrd Inattention (Inattentive), Details Unknown 1 1 1 1 1 1 NA NA NA NA
mdrdstrd Looked But Did Not See 1 1 1 1 NA NA NA NA NA NA
drdistract Lost in Thought / Day dreaming NA NA NA NA NA NA 1 1 1 1
mdrdstrd Lost in Thought / Day dreaming 1 1 1 1 1 1 NA NA NA NA
drdistract No Driver Present/Unknown if Driver present NA NA NA NA NA NA 1 1 1 1
mdrdstrd No Driver Present/Unknown if Driver present 1 1 1 1 1 1 NA NA NA NA
drdistract Not Distracted NA NA NA NA NA NA 1 1 1 1
mdrdstrd Not Distracted 1 1 1 1 1 1 NA NA NA NA
drdistract Not Reported NA NA NA NA NA NA 1 1 1 1
mdrdstrd Not Reported 1 1 1 1 1 1 NA NA NA NA
mdrdstrd Other Cellular Phone Related 1 1 1 1 1 NA NA NA NA NA
mdrdstrd Other Distraction 1 1 1 1 1 NA NA NA NA NA
drdistract Other Distraction [Specify:] NA NA NA NA NA NA 1 1 1 1
mdrdstrd Other Distraction [Specify:] NA NA NA NA NA 1 NA NA NA NA
drdistract Other Mobile Phone Related NA NA NA NA NA NA 1 1 1 1
mdrdstrd Other Mobile Phone Related NA NA NA NA NA 1 NA NA NA NA
drdistract Reported as Unknown if Distracted NA NA NA NA NA NA 1 1 1 1
mdrdstrd Reported as Unknown if Distracted NA NA NA NA 1 1 NA NA NA NA
drdistract Smoking Related NA NA NA NA NA NA 1 1 1 1
mdrdstrd Smoking Related 1 1 1 1 1 1 NA NA NA NA
mdrdstrd Unknown if Distracted 1 1 1 1 NA NA NA NA NA NA
mdrdstrd While Manipulating Cellular Phone 1 1 1 1 1 NA NA NA NA NA
drdistract While Manipulating Mobile Phone NA NA NA NA NA NA 1 1 1 1
mdrdstrd While Manipulating Mobile Phone NA NA NA NA NA 1 NA NA NA NA
mdrdstrd While Talking or Listening to Cellular Phone 1 1 1 1 1 NA NA NA NA NA
drdistract While Talking or Listening to Mobile Phone NA NA NA NA NA NA 1 1 1 1
mdrdstrd While Talking or Listening to Mobile Phone NA NA NA NA NA 1 NA NA NA NA
drdistract While Using or Reaching for Device/Object Brought into Vehicle NA NA NA NA NA NA 1 1 1 1
mdrdstrd While Using or Reaching for Device/Object Brought into Vehicle 1 1 1 1 1 1 NA NA NA NA
drdistract While Using Other Component/Controls Integral to Vehicle NA NA NA NA NA NA 1 1 1 1
mdrdstrd While Using Other Component/Controls Integral to Vehicle 1 1 1 1 1 1 NA NA NA NA

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")
name_rfars value_label 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
per_typ Bicyclist 1 1 1 1 1 1 1 1 1 1
per_typ Driver of a Motor Vehicle In-Transport 1 1 1 1 1 1 1 1 1 1
per_typ Occupant of a Motor Vehicle Not In- Transport 1 1 1 1 1 1 1 1 1 1
per_typ Occupant of a Non-Motor Vehicle Transport Device 1 1 1 1 1 1 1 1 1 1
per_typ Other Cyclist 1 1 1 1 1 1 1 1 NA NA
per_typ Other Pedalcyclist NA NA NA NA NA NA NA NA 1 1
per_typ Passenger of a Motor Vehicle In-Transport 1 1 1 1 1 1 1 1 1 1
per_typ Pedestrian 1 1 1 1 1 1 1 1 1 1
per_typ Person In/On a Building NA NA NA NA NA NA NA NA 1 1
per_typ Person on a Personal Conveyance NA NA NA NA NA NA NA NA 1 1
per_typ Person on Motorized Personal Conveyance NA NA NA NA NA NA 1 1 NA NA
per_typ Person on Motorized Personal Conveyance NA NA NA NA NA NA NA NA 1 NA
per_typ Person on Non-Motorized Personal Conveyance NA NA NA NA NA NA 1 1 1 NA
per_typ Person on Personal Conveyance, Unknown if Motorized or Non-Motorized NA NA NA NA NA NA 1 1 NA NA
per_typ Person on Personal Conveyance, Unknown if Motorized or Non-Motorized*/ NA NA NA NA NA NA NA NA 1 NA
per_typ Person on Personal Conveyances NA NA NA 1 1 1 NA NA NA NA
per_typ Persons In/On Buildings 1 1 1 1 1 1 1 1 NA NA
per_typ Persons on Personal Conveyances 1 1 1 NA NA NA NA NA NA NA
per_typ Unknown Occupant Type in a Motor Vehicle In- Transport 1 1 1 1 1 1 1 1 1 1
per_typ Unknown Type of Non-Motorist 1 1 1 1 1 1 1 1 1 1

Users of rfars and FARS data in general are strongly encouraged to User Manuals for further guidance.