RATETest {EpiForsk}

wrapper for rank_average_treatment_effect

Description

Provides confidence interval and p-value together with the standard output from rank_average_treatment_effect.

Usage

RATETest(
  forest,
  priorities,
  level = 0.95,
  cov_type = c("continuous", "discrete"),
  target = "AUTOC",
  q = seq(0.1, 1, by = 0.1),
  R = 500,
  subset = NULL,
  debiasing.weights = NULL,
  compliance.score = NULL,
  num.trees.for.weights = 500
)

Arguments

forest

An object of class causal_forest, as returned by causal_forest().

priorities

character, name of covariate to test for heterogeneity.

level

numeric, level of RATE confidence interval.

cov_type

character, either "continuous" or "discrete". If "discrete", and q is not manually set, TOC will be evaluated at the quantiles corresponding to transitions from one level to the next.

target

character, see rank_average_treatment_effect.

q

numeric, see rank_average_treatment_effect.

R

integer, see rank_average_treatment_effect.

subset

numeric, see rank_average_treatment_effect.

debiasing.weights

numeric, see rank_average_treatment_effect.

compliance.score

numeric, see rank_average_treatment_effect.

num.trees.for.weights

integer, see rank_average_treatment_effect.

Value

A list of class 'rank_average_treatment_effect' with elements

• estimate: the RATE estimate.

• std.err: bootstrapped standard error of RATE.

• target: the type of estimate.

• TOC: a data.frame with the Targeting Operator Characteristic curve estimated on grid q, along with bootstrapped SEs.

• confint: a data.frame with the lower and upper bounds of the RATE confidence interval.

• pval: the p-value for the test that RATE is non-positive.

Author(s)

KIJA

Examples

n <- 800
p <- 3
X <- matrix(rnorm(n * p), n, p)
W <- rbinom(n, 1, 0.5)
event_prob <- 1 / (1 + exp(2 * (pmax(2 * X[, 1], 0) * W - X[, 2])))
Y <- rbinom(n, 1, event_prob)
cf <- grf::causal_forest(X, Y, W)
rate <- RATETest(cf, 1)
rate$pval