Thin wrapper around DRDID::drdid_rc for the 2x2
repeated-cross-section setting. Combines an outcome regression
model with an inverse-probability weighting model and is
consistent if either model is correctly specified. Hard-errors if
DRDID is not installed.
Usage
morie_did_doubly_robust(
data,
outcome,
treatment,
post,
covariates,
ps_model = "logistic",
or_model = "linear",
cluster = NULL,
n_bootstrap = 200L,
seed = 42L,
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.
- ps_model
Unused; retained for back-compat. DRDID fits a logistic propensity-score model internally.
- or_model
Unused; retained for back-compat. DRDID fits a linear outcome model internally.
- cluster
Optional cluster ID column for CR1 standard errors.
- n_bootstrap
Number of bootstrap replications (forwarded as
nboot).- seed
RNG seed (set before the call).
- alpha
Significance level for confidence intervals (default 0.05).
Value
A result list; see morie_did_2x2.
Details
For panel data (same units observed in both periods) prefer
DRDID::drdid_panel directly.