This repository contains the data and code that generate the figures in the article: A Hierarchical Bayes Approach to Adjust for Selection Bias in Before-After Analyses of Vision Zero Policies. Some general comments about the data and code are necessary.
The data are contained in the directory /data. Some datasets, such as shapefiles, are too large to be uploaded to github. (See https://help.github.com/en/articles/what-is-my-disk-quota for details.) Commented code links to the location of these datasets. To download the data, simply use the download.file and unzip functions.
For example, the comments state that the New York street shapefile can be found at http://gis.ny.gov/gisdata/inventories/details.cfm?DSID=932. To download this data, run
url <- "http://gis.ny.gov/gisdata/fileserver/?DSID=932&file=streets_shp.zip"
download.file(url, destfile = "data/Vision_Zero/streets_shp.zip")
unzip("data/Vision_Zero/streets_shp.zip", exdir = "data/Vision_Zero")
file.remove("data/Vision_Zero/streets_shp.zip")
streets <- rgdal::readOGR("data/Vision_Zero/Streets_shp/", "StreetSegment")
The code is contained in one script bayes_approach_selection_bias.R and divided into 12 steps.
It was written in 2017 using R 3.3 and RStan 2.14.
The code uses the ggmap function get_map, which as of 2018 requires an API key from Google. Be sure to install ggmap using the devtools package: devtools::install_github("dkahle/ggmap") in Step 1: Setup. (See https://www.r-bloggers.com/geocoding-with-ggmap-and-the-google-api/ for details.)
For example,
devtools::install_github("dkahle/ggmap")
library("ggmap")
api_key <- "your key here"
ggmap::register_google(key = api_key)
ggmap::has_google_key()