rdmcplot: Data-driven RD plots for multi-cutoff designs

In rdmulti: Robust Local Polynomial Methods for RD Designs with Multiple Cutoffs or Multiple Scores

Data-driven RD plots for multi-cutoff designs

Description

rdmcplot() implements data-driven Regression Discontinuity (RD) plots for designs with multiple cutoffs.

Usage

rdmcplot(
  Y,
  X,
  C,
  nbinsmat = NULL,
  binselectvec = NULL,
  scalevec = NULL,
  supportmat = NULL,
  pvec = NULL,
  hmat = NULL,
  kernelvec = NULL,
  weightsvec = NULL,
  covs_mat = NULL,
  covs_list = NULL,
  covs_evalvec = NULL,
  covs_dropvec = NULL,
  ginv.tolvec = NULL,
  masspointsvec = NULL,
  ci = NULL,
  shade = FALSE,
  col_bins = NULL,
  pch_bins = NULL,
  col_poly = NULL,
  lty_poly = NULL,
  col_xline = NULL,
  lty_xline = NULL,
  nobins = FALSE,
  nopoly = FALSE,
  noxline = FALSE,
  nodraw = FALSE,
  subset = NULL,
  data = NULL
)

Arguments

Y	outcome variable.
X	running variable.
C	cutoff variable.
nbinsmat	matrix of cutoff-specific number of bins. See rdplot() for details.
binselectvec	vector of cutoff-specific bins selection method. See rdplot() for details.
scalevec	vector of cutoff-specific scale factors. See rdplot() for details.
supportmat	matrix of cutoff-specific support conditions. See rdplot() for details..
pvec	vector of cutoff-specific polynomial orders. See rdplot() for details.
hmat	matrix of cutoff-specific bandwidths. See rdplot() for details.
kernelvec	vector of cutoff-specific kernels. See rdplot() for details.
weightsvec	vector of cutoff-specific weights. See rdplot() for details.
covs_mat	matrix of covariates. See rdplot() for details.
covs_list	list of of covariates to be used in each cutoff.
covs_evalvec	vector indicating the evaluation point for additional covariates. See rdrobust() for details.
covs_dropvec	vector indicating whether collinear covariates should be dropped at each cutoff. See rdrobust() for details.
ginv.tolvec	vector of cutoff-specific tolerances for generalized inverse calculations. See rdplot() for details.
masspointsvec	vector indicating how to handle repeated values at each cutoff. See rdplot() for details.
ci	adds confidence intervals of the specified level to the plot. See rdrobust() for details.
shade	passes the shaded confidence interval option to rdplot().
col_bins	vector of colors for bins.
pch_bins	vector of characters (pch) type for bins.
col_poly	vector of colors for polynomial curves.
lty_poly	vector of lty for polynomial curves.
col_xline	vector of colors for vertical lines.
lty_xline	vector of lty for vertical lines.
nobins	omits bins plot.
nopoly	omits polynomial curve plot.
noxline	omits vertical lines indicating the cutoffs.
nodraw	omits plot.
subset	optional subset of observations to use.
data	optional data frame for resolving string variable names.

Value

clist	list of cutoffs
cnum	number of cutoffs
X0	matrix of X values for control units
X1	matrix of X values for treated units
Yhat0	estimated polynomial for control units
Yhat1	estimated polynomial for treated units
Xmean	bin average of X values
Ymean	bin average for Y values
CI_l	lower end of confidence intervals
CI_r	upper end of confidence intervals
cfail	Cutoffs where rdrobust() encountered problems

Author(s)

Matias D. Cattaneo, Princeton University. [e-mail]

Rocio Titiunik, Princeton University. [e-mail]

Gonzalo Vazquez-Bare, UC Santa Barbara. [e-mail]

References

Cattaneo, M.D., R. Titiunik and G. Vazquez-Bare. (2020). Analysis of Regression Discontinuity Designs with Multiple Cutoffs or Multiple Scores. Stata Journal, forthcoming.

Examples

# Toy dataset
X <- runif(1000,0,100)
C <- c(rep(33,500),rep(66,500))
Y <- (1 + X + (X>=C))*(C==33)+(.5 + .5*X + .8*(X>=C))*(C==66) + rnorm(1000)
# rdmcplot with standard syntax
tmp <- rdmcplot(Y,X,C)

rdmulti documentation built on May 18, 2026, 1:07 a.m.