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Plot the Regression Discontinuity

plot.rd.Rd

plot.rd plots the relationship between the running variable and the outcome. It is based on the plot.RD function in the "rdd" package.

Usage

# S3 method for rd
plot(
  x,
  preds = NULL,
  fit_line = c("linear", "quadratic", "cubic", "optimal", "half", "double"),
  fit_ci = c("area", "dot", "hide"),
  fit_ci_level = 0.95,
  bin_n = 20,
  bin_level = 0.95,
  bin_size = c("shade", "size"),
  quant_bin = TRUE,
  xlim = NULL,
  ylim = NULL,
  include_rugs = FALSE,
  ...
)

Arguments

x

An rd object, typically the result of rd_est.

preds

An optional vector of predictions generated by predict.rd. If not supplied, prediction is completed within the plot.rd function.

fit_line

A character vector specifying models to be shown as fitted lines. Options are c("linear", "quadratic", "cubic", "optimal", "half", "double").

fit_ci

A string specifying whether and how to plot prediction confidence intervals around the fitted lines. Options are c("area", "dot", "hide").

fit_ci_level

A numeric value between 0 and 1 specifying the confidence level of prediction CIs. The default is 0.95.

bin_n

An integer specifying the number of bins for binned data points. If bin_n is 0, raw data points are plotted. If bin_n is < 0, data points are suppressed. The default is 20.

bin_level

A numeric value between 0 and 1 specifying the confidence level for CIs around binned data points. The default is 0.95.

bin_size

A string specifying how to plot the number of observations in each bin, by "size" or "shape".

quant_bin

A logical value indicating whether the data are binned by quantiles. The default is TRUE.

xlim

An optional numeric vector containing the x-axis limits.

ylim

An optional numeric vector containing the y-axis limits.

include_rugs

A logical value indicating whether to include the 1d plot for both axes. The default is FALSE.

...

Additional graphic arguments passed to plot.

References

Drew Dimmery (2016). rdd: Regression Discontinuity Estimation. R package version 0.57. https://CRAN.R-project.org/package=rdd

Examples

set.seed(12345) 
dat <- data.frame(x = runif(1000, -1, 1), cov = rnorm(1000))
dat$tr <- as.integer(dat$x >= 0)
dat$y <- 3 + 2 * dat$x + 3 * dat$cov + 10 * (dat$x >= 0) + rnorm(1000)
rd <- rd_est(y ~ x + tr | cov, data = dat, cutpoint = 0, t.design = "geq") 
plot(rd)