Repeated cross-section DiD (optionally weighted) — morie_did_repeated_cross

Same specification as morie_did_2x2 but accepts a survey weight column. When weights is supplied, weighted least squares is used.

Usage

morie_did_repeated_cross_section(
  data,
  outcome,
  treatment,
  post,
  covariates = NULL,
  weights = NULL,
  cluster = NULL,
  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.
covariates: Optional character vector of covariate column names.
weights: Optional column of (sampling / survey) weights.
cluster: Optional cluster ID column for CR1 standard errors.
alpha: Significance level for confidence intervals (default 0.05).

Value

A list of class results; see morie_did_2x2.

Examples

set.seed(1)
n <- 400
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,
                 w = runif(n, 0.5, 2))
res <- morie_did_repeated_cross_section(df, "y", "d", "post",
                                        weights = "w")
res$estimate
#> [1] 0.5353118