Simulated example data for assessing race bias in traffic stop outcomes
A data frame with 5000 observations on the following 10 variables.
an ID for each traffic stop
a factor indicating the neighborhood in which the stop occurred.
The reason for the stop, mechanical/registration violations, dangerous moving violation, non-dangerous moving violation
an indicator whether the driver is a resident of the city
an indicator whether the driver was male
the race of the driver, with levels
the hour of the stop (24-hour clock)
and ordered factor indicating in which month the stop took place
an 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).
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