Fuzzy RDD treatment effect via instrumented Wald ratio

Usage

morie_rdd_fuzzy(
  data,
  outcome,
  running,
  treatment,
  cutoff = 0,
  bandwidth = NULL,
  p = 1,
  kernel = "triangular",
  alpha = 0.05
)

Arguments

data: A data.frame holding the outcome, running variable, treatment, and any covariates referenced by name.
outcome: Character; column name of the response variable in data.
running: Character; column name of the running (forcing) variable in data.
treatment: Character; column name of the treatment-receipt variable (fuzzy designs).
cutoff: Numeric scalar; the threshold on running. Default 0 (the canonical normalisation).
bandwidth: Numeric; the local-polynomial bandwidth on each side of the cutoff. NULL invokes the data-driven CCT selector.
p: Integer; local-polynomial order (default 1 for local- linear). 2 picks up quadratic curvature for bias correction.
kernel: One of "triangular" (default), "epanechnikov", "uniform", or "gaussian".
alpha: Significance level (default 0.05).

Value

A named list with elements estimate, std_error, t_stat, p_value, ci_lower, ci_upper, n_obs, method, details.

Examples

set.seed(34)
n <- 1000
x <- runif(n, -1, 1)
tr <- as.integer(xor(x >= 0, rbinom(n, 1, 0.1) == 1))
y <- 0.3 * x + 1.5 * tr + rnorm(n, sd = 0.5)
d <- data.frame(y, x, tr)
res <- morie_rdd_fuzzy(d, outcome = "y", running = "x",
                       treatment = "tr", cutoff = 0)
res$estimate
#> [1] 1.431063