rdms {rdmulti} | R Documentation |
Analysis of RD designs with cumulative cutoffs or two running variables
Description
rdms()
analyzes RD designs with cumulative cutoffs or two running variables.
Usage
rdms(
Y,
X,
C,
X2 = NULL,
zvar = NULL,
C2 = NULL,
rangemat = NULL,
xnorm = NULL,
fuzzy = NULL,
derivvec = NULL,
pooled_opt = NULL,
pvec = NULL,
qvec = NULL,
hmat = NULL,
bmat = NULL,
rhovec = NULL,
covs_mat = NULL,
covs_list = NULL,
covs_dropvec = NULL,
kernelvec = NULL,
weightsvec = NULL,
bwselectvec = NULL,
scaleparvec = NULL,
scaleregulvec = NULL,
masspointsvec = NULL,
bwcheckvec = NULL,
bwrestrictvec = NULL,
stdvarsvec = NULL,
vcevec = NULL,
nnmatchvec = NULL,
cluster = NULL,
level = 95,
plot = FALSE,
conventional = FALSE
)
Arguments
Y |
outcome variable. |
X |
running variable. |
C |
vector of cutoffs. |
X2 |
if specified, second running variable. |
zvar |
if X2 is specified, treatment indicator. |
C2 |
if specified, second vector of cutoffs. |
rangemat |
matrix of cutoff-specific ranges for the running variable. |
xnorm |
normalized running variable to estimate pooled effect. |
fuzzy |
specifies a fuzzy design. See |
derivvec |
vector of cutoff-specific order of derivatives. See
|
pooled_opt |
options to be passed to |
pvec |
vector of cutoff-specific polynomial orders. See
|
qvec |
vector of cutoff-specific polynomial orders for bias estimation.
See |
hmat |
matrix of cutoff-specific bandwidths. See |
bmat |
matrix of cutoff-specific bandwidths for bias estimation. See
|
rhovec |
vector of cutoff-specific values of rho. See |
covs_mat |
matrix of covariates. See |
covs_list |
list of of covariates to be used in each cutoff. |
covs_dropvec |
vector indicating whether collinear covariates should be
dropped at each cutoff. See |
kernelvec |
vector of cutoff-specific kernels. See |
weightsvec |
vector of length equal to the number of cutoffs indicating
the names of the variables to be used as weights in each cutoff. See |
bwselectvec |
vector of cutoff-specific bandwidth selection methods. See
|
scaleparvec |
vector of cutoff-specific scale parameters. See
|
scaleregulvec |
vector of cutoff-specific scale regularization
parameters. See |
masspointsvec |
vector indicating how to handle repeated values at each
cutoff. See |
bwcheckvec |
vector indicating the value of bwcheck at each cutoff. See
|
bwrestrictvec |
vector indicating whether computed bandwidths are
restricted to the range or runvar at each cutoff. See |
stdvarsvec |
vector indicating whether variables are standardized at
each cutoff. See |
vcevec |
vector of cutoff-specific variance-covariance estimation
methods. See |
nnmatchvec |
vector of cutoff-specific nearest neighbors for variance
estimation. See |
cluster |
cluster ID variable. See |
level |
confidence level for confidence intervals. See |
plot |
plots cutoff-specific and pooled estimates. |
conventional |
reports conventional, instead of robust-bias corrected, p-values and confidence intervals. |
Value
B |
vector of bias-corrected coefficients |
V |
variance-covariance matrix of the estimators |
Coefs |
vector of conventional coefficients |
Nh |
vector of sample sizes within bandwidth at each cutoff |
CI |
bias corrected confidence intervals |
H |
bandwidth used at each cutoff |
Pv |
vector of robust p-values |
Author(s)
Matias Cattaneo, Princeton University. cattaneo@princeton.edu
Rocio Titiunik, Princeton University. titiunik@princeton.edu
Gonzalo Vazquez-Bare, UC Santa Barbara. gvazquez@econ.ucsb.edu
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: cumulative cutoffs
X <- runif(1000,0,100)
C <- c(33,66)
Y <- (1+X)*(X<C[1])+(0.8+0.8*X)*(X>=C[1]&X<C[2])+(1.2+1.2*X)*(X>=C[2]) + rnorm(1000)
# rmds: basic syntax
tmp <- rdms(Y,X,C)