Replicate a DDML Estimator Across Multiple Resamples

Convenience wrapper that calls a ddml_* estimator function multiple times with independent sample splits and returns a ddml_rep object for aggregated inference.

Usage

ddml_replicate(fn, ..., resamples = 5, silent = FALSE)

Arguments

fn

A ddml_* estimator function (e.g., ddml_plm).

...

Arguments passed to fn.

resamples

Integer number of independent resamples. Must be >= 2. Default 5.

silent

Logical. If TRUE, suppresses all output at both the resample level and within each estimator call. Default FALSE.

Value

An object of class "ddml_rep".

See also

ddml_rep()

Other ddml replication: ddml_rep()

Examples

# \donttest{
y = AE98[, "worked"]
D = AE98[, "morekids"]
X = AE98[, c("age","agefst","black","hisp","othrace")]
reps = ddml_replicate(ddml_plm, y = y, D = D, X = X,
                      learners = list(what = ols),
                      sample_folds = 2,
                      resamples = 3, silent = TRUE)
summary(reps)
#> DDML estimation: Partially Linear Model 
#> Obs: 5000   Folds: 2   Resamples: 3   Aggregation: median
#> 
#>              Estimate Std. Error z value Pr(>|z|)    
#> D1          -0.155060   0.014738  -10.52   <2e-16 ***
#> (Intercept) -0.000106   0.006947   -0.02     0.99    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# }