Staggered DiD via group-time ATTs with aggregation — morie_did

Convenience wrapper around morie_did_group_time_att and morie_did_aggregate_gt_att.

Usage

morie_did_staggered(
  data,
  outcome,
  unit,
  time,
  treatment_time,
  covariates = NULL,
  n_bootstrap = 200L,
  seed = 42L,
  alpha = 0.05
)

Arguments

data: Panel data.
outcome: Outcome column.
unit: Unit identifier.
time: Calendar-time column (integer).
treatment_time: Column with treatment-onset period (use Inf for never-treated).
covariates: Optional covariates for doubly-robust estimation.
n_bootstrap: Number of multiplier-bootstrap replications for inference (0 = analytic influence-function standard errors).
seed: RNG seed for the multiplier bootstrap.
alpha: Significance level.

Value

A list with group_time, overall, by_cohort, by_event_time.

Examples

set.seed(2)
df <- expand.grid(unit = 1:40, time = 1:6)
df$treat_time <- ifelse(df$unit <= 20, 4, Inf)
df$d <- as.integer(df$time >= df$treat_time)
df$y <- 0.1 * df$time + 0.6 * df$d + rnorm(nrow(df), sd = 0.4)
out <- morie_did_staggered(df, "y", "unit", "time", "treat_time",
                           n_bootstrap = 50L, seed = 2)
str(out, max.level = 1)
#> List of 4
#>  $ group_time   :'data.frame':	5 obs. of  7 variables:
#>   ..- attr(*, "fit")=List of 3
#>  $ overall      :'data.frame':	1 obs. of  5 variables:
#>  $ by_cohort    :'data.frame':	1 obs. of  5 variables:
#>  $ by_event_time:'data.frame':	5 obs. of  5 variables: