nassCDS: Airbag and other influences on accident fatalities
In DAAG: Data Analysis and Graphics Data and Functions

nassCDS

R Documentation

Airbag and other influences on accident fatalities

Description

US data, for 1997-2002, from police-reported car crashes in which there is a harmful event (people or property), and from which at least one vehicle was towed. Data are restricted to front-seat occupants, include only a subset of the variables recorded, and are restricted in other ways also.

Usage

nassCDS

Format

A data frame with 26217 observations on the following 15 variables.

dvcat: ordered factor with levels (estimated impact speeds) 1-9km/h, 10-24, 25-39, 40-54, 55+
weight: Observation weights, albeit of uncertain accuracy, designed to account for varying sampling probabilities.
dead: factor with levels alive dead
airbag: a factor with levels none airbag
seatbelt: a factor with levels none belted
frontal: a numeric vector; 0 = non-frontal, 1=frontal impact
sex: a factor with levels f m
ageOFocc: age of occupant in years
yearacc: year of accident
yearVeh: Year of model of vehicle; a numeric vector
abcat: Did one or more (driver or passenger) airbag(s) deploy? This factor has levels deploy nodeploy unavail
occRole: a factor with levels driver pass
deploy: a numeric vector: 0 if an airbag was unavailable or did not deploy; 1 if one or more bags deployed.
injSeverity: a numeric vector; 0:none, 1:possible injury, 2:no incapacity, 3:incapacity, 4:killed; 5:unknown, 6:prior death
caseid: character, created by pasting together the populations sampling unit, the case number, and the vehicle number. Within each year, use this to uniquely identify the vehicle.

Details

Data collection used a multi-stage probabilistic sampling scheme. The observation weight, called national inflation factor (national) in the data from NASS, is the inverse of an estimate of the selection probability. These data include a subset of the variables from the NASS dataset. Variables that are coded here as factors are coded as numeric values in that dataset.

Source

https://www.stat.colostate.edu/~meyer/airbags.htm\ https://www.nhtsa.gov/file-downloads

References

Meyer, M.C. and Finney, T. (2005): Who wants airbags?. Chance 18:3-16.

Farmer, C.H. 2006. Another look at Meyer and Finney's ‘Who wants airbags?’. Chance 19:15-22.

Meyer, M.C. 2006. Commentary on "Another look at Meyer and Finney's ‘Who wants airbags?’. Chance 19:23-24.

For analyses based on the alternative FARS (Fatal Accident Recording System) data, and associated commentary, see:

Cummings, P; McKnight, B, 2010. Accounting for vehicle, crash, and occupant characteristics in traffic crash studies. Injury Prevention 16: 363-366. [The relatively definitive analyses in this paper use a matched cohort design,

Olson, CM; Cummings, P, Rivara, FP, 2006. Association of first- and second-generation air bags with front occupant death in car crashes: a matched cohort study. Am J Epidemiol 164:161-169. [The relatively definitive analyses in this paper use a matched cohort design, using data taken from the FARS (Fatal Accident Recording System) database.]

Braver, ER; Shardell, M; Teoh, ER, 2010. How have changes in air bag designs affected frontal crash mortality? Ann Epidemiol 20:499-510.

The web page https://www-fars.nhtsa.dot.gov/Main/index.aspx has a menu-based interface into the FARS (Fatality Analysis Recording System) data. The FARS database aims to include every accident in which there was at least one fatality.

Examples

data(nassCDS)
xtabs(weight ~ dead + airbag, data=nassCDS)
xtabs(weight ~ dead + airbag + seatbelt + dvcat, data=nassCDS)
tab <- xtabs(weight ~ dead + abcat, data=nassCDS,
             subset=dvcat=="25-39"&frontal==0)[, c(3,1,2)]
round(tab[2, ]/apply(tab,2,sum)*100,2)

DAAG documentation built on May 29, 2024, 9:13 a.m.