rdrbounds {rdlocrand} | R Documentation |
Rosenbaum bounds for RD designs under local randomization
Description
rdrbounds
calculates lower and upper bounds for the
randomization p-value under different degrees of departure from a
local randomized experiment, as suggested by Rosenbaum (2002).
Usage
rdrbounds(
Y,
R,
cutoff = 0,
wlist,
gamma,
expgamma,
bound = "both",
statistic = "ranksum",
p = 0,
evalat = "cutoff",
kernel = "uniform",
fuzzy = NULL,
nulltau = 0,
prob,
fmpval = FALSE,
reps = 1000,
seed = 666
)
Arguments
Y |
a vector containing the values of the outcome variable. |
R |
a vector containing the values of the running variable. |
cutoff |
the RD cutoff (default is 0). |
wlist |
the list of window lengths to be evaluated. By default the program constructs 10 windows around the cutoff, the first one including 10 treated and control observations and adding 5 observations to each group in subsequent windows. |
gamma |
the list of values of gamma to be evaluated. |
expgamma |
the list of values of exp(gamma) to be evaluated. Default is |
bound |
specifies which bounds the command calculates. Options are |
statistic |
the statistic to be used in the balance tests. Allowed options are |
p |
the order of the polynomial for outcome adjustment model. Default is 0. |
evalat |
specifies the point at which the adjusted variable is evaluated. Allowed options are |
kernel |
specifies the type of kernel to use as weighting scheme. Allowed kernel types are |
fuzzy |
indicates that the RD design is fuzzy. |
nulltau |
the value of the treatment effect under the null hypothesis. Default is 0. |
prob |
the probabilities of treatment for each unit when assignment mechanism is a Bernoulli trial. This option should be specified as a vector of length equal to the length of the outcome and running variables. |
fmpval |
reports the p-value under fixed margins randomization, in addition to the p-value under Bernoulli trials. |
reps |
number of replications. Default is 1000. |
seed |
the seed to be used for the randomization tests. |
Value
gamma |
list of gamma values. |
expgamma |
list of exp(gamma) values. |
wlist |
window grid. |
p.values |
p-values for each window (under gamma = 0). |
lower.bound |
list of lower bound p-values for each window and gamma pair. |
upper.bound |
list of upper bound p-values for each window and gamma pair. |
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. (2016). Inference in Regression Discontinuity Designs under Local Randomization. Stata Journal 16(2): 331-367.
Rosenbaum, P. (2002). Observational Studies. Springer.
Examples
# Toy dataset
R <- runif(100,-1,1)
Y <- 1 + R -.5*R^2 + .3*R^3 + (R>=0) + rnorm(100)
# Rosenbaum bounds
# Note: low number of replications and windows to speed up process.
# The user should increase these values.
rdrbounds(Y,R,expgamma=c(1.5,2),wlist=c(.3),reps=100)