Bandwidth sensitivity sweep

Usage

morie_rdd_bandwidth_sensitivity(
  data,
  outcome,
  running,
  cutoff = 0,
  bandwidth_range = 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.
cutoff: Numeric scalar; the threshold on running. Default 0 (the canonical normalisation).
bandwidth_range: Numeric vector of candidate bandwidths used by the sensitivity analysis.
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 data.frame of RDD estimates across bandwidths, one row per bandwidth.

Examples

set.seed(1)
x <- runif(400, -1, 1)
y <- 0.3 * x + 1.0 * (x >= 0) + rnorm(400, sd = 0.3)
d <- data.frame(x, y)
out <- morie_rdd_bandwidth_sensitivity(d, "y", "x")
out
#>     bandwidth estimate std_error      p_value  ci_lower ci_upper
#> 1  0.07544647 1.338187 0.3264025 4.134958e-05 0.6984500 1.977924
#> 2  0.10059529 1.300020 0.2922243 8.638926e-06 0.7272708 1.872769
#> 3  0.12574412 1.232117 0.2550881 1.364220e-06 0.7321533 1.732080
#> 4  0.15089294 1.158346 0.2268739 3.295996e-07 0.7136818 1.603011
#> 5  0.17604177 1.113400 0.2098670 1.125087e-07 0.7020686 1.524732
#> 6  0.20119059 1.105325 0.1952651 1.508110e-08 0.7226126 1.488038
#> 7  0.22633941 1.118786 0.1812321 6.691344e-10 0.7635772 1.473994
#> 8  0.25148824 1.123174 0.1713955 5.635084e-11 0.7872448 1.459103
#> 9  0.27663706 1.114098 0.1625117 7.106695e-12 0.7955809 1.432615
#> 10 0.30178588 1.100946 0.1547179 1.112452e-12 0.7977042 1.404187