| raceprofiling | R Documentation |
Simulated example data for assessing race bias in traffic stop outcomes
data(raceprofiling)
A data frame with 5000 observations on the following 10 variables.
idan ID for each traffic stop
nhooda factor indicating the neighborhood in which the stop occurred.
reasonThe reason for the stop, mechanical/registration violations, dangerous moving violation, non-dangerous moving violation
residentan indicator whether the driver is a resident of the city
agedriver's age
malean indicator whether the driver was male
racethe race of the driver, with levels A, B,
H, W
hourthe hour of the stop (24-hour clock)
monthand ordered factor indicating in which month the stop took place
citationan indicator of whether the driver received a citation
This is simulated data to demonstrate how to use twang to adjust
estimates of racial bias for important factors. This dataset does not represent
real data from any real law enforcement agency.
G. Ridgeway (2006). “Assessing the effect of race bias in post-traffic stop outcomes using propensity scores,” Journal of Quantitative Criminology 22(1).
data(raceprofiling)
# the first five lines of the dataset
raceprofiling[1:5,]
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