printspatialrd: Print spatialrd output

In axlehner/SpatialRDD: Conduct Multiple Types of Geographic Regression Discontinuity Designs

Print spatialrd output

Description

Preliminary function, styling with e.g. kable and kableExtra has to be done by the user individually. You could also just use the package of your choice to print out columns of the output from spatialrd.

Usage

printspatialrd(SpatialRDoutput)

Arguments

SpatialRDoutput

output file from the spatialrd function

Value

A table with results from the spatialrd function

Examples

points_samp.sf <- sf::st_sample(polygon_full, 1000) # create points
# make it an sf object bc st_sample only created the geometry list-column (sfc):
points_samp.sf <- sf::st_sf(points_samp.sf)
# add a unique ID to each observation:
points_samp.sf$id <- 1:nrow(points_samp.sf)
# assign treatment:
points_samp.sf$treated <- assign_treated(points_samp.sf, polygon_treated, id = "id")
# first we define a variable for the number of "treated" and control
NTr <- length(points_samp.sf$id[points_samp.sf$treated == 1])
NCo <- length(points_samp.sf$id[points_samp.sf$treated == 0])
# the treated areas get a 10 percentage point higher literacy rate
points_samp.sf$education[points_samp.sf$treated == 1] <- 0.7
points_samp.sf$education[points_samp.sf$treated == 0] <- 0.6
# and we add some noise, otherwise we would obtain regression coeffictions with no standard errors
points_samp.sf$education[points_samp.sf$treated == 1] <- rnorm(NTr, mean = 0, sd = .1) +
  points_samp.sf$education[points_samp.sf$treated == 1]
points_samp.sf$education[points_samp.sf$treated == 0] <- rnorm(NCo, mean = 0, sd = .1) +
  points_samp.sf$education[points_samp.sf$treated == 0]

# create distance to cutoff
points_samp.sf$dist2cutoff <- as.numeric(sf::st_distance(points_samp.sf, cut_off))

points_samp.sf$distrunning <- points_samp.sf$dist2cutoff
# give the non-treated one's a negative score
points_samp.sf$distrunning[points_samp.sf$treated == 0] <- -1 *
 points_samp.sf$distrunning[points_samp.sf$treated == 0]

# create borderpoints
borderpoints.sf <- discretise_border(cutoff = cut_off, n = 10)
borderpoints.sf$id <- 1:nrow(borderpoints.sf)

# finally, carry out estimation alongside the boundary:
results <- spatialrd(y = "education", data = points_samp.sf, cutoff.points = borderpoints.sf,
treated = "treated", minobs = 20, spatial.object = FALSE)
printspatialrd(results)

axlehner/SpatialRDD documentation built on March 24, 2024, 2:03 p.m.