Heterogeneity-robust DiD by sub-group / moderator quantile — morie_did

Splits the sample by quantiles (or categories) of a moderator and estimates separate 2x2 DiDs.

Usage

morie_did_heterogeneous(
  data,
  outcome,
  treatment,
  post,
  moderator,
  covariates = NULL,
  cluster = NULL,
  n_quantiles = 4L,
  alpha = 0.05
)

Arguments

data: A data frame containing the outcome, treatment, post and any covariate columns.
outcome: Name of the outcome column.
treatment: Name of the binary (0/1) treatment-group column.
post: Name of the binary (0/1) post-period column.
moderator: Column to split on.
covariates: Optional character vector of covariate column names.
cluster: Optional cluster ID column for CR1 standard errors.
n_quantiles: Number of quantile bins if the moderator is continuous.
alpha: Significance level for confidence intervals (default 0.05).

Value

A data frame with one row per stratum.

Examples

if (morie_crypto_liboqs_available()) {
  set.seed(1)
  n <- 600
  d <- rbinom(n, 1, 0.5)
  p <- rbinom(n, 1, 0.5)
  y <- 1 + 0.3 * d + 0.4 * p + 0.5 * d * p + rnorm(n, sd = 0.5)
  df <- data.frame(y = y, d = d, post = p, mod = rnorm(n))
  out <- morie_did_heterogeneous(df, "y", "d", "post",
    moderator = "mod", n_quantiles = 3L
  )
  out
}