Summary for DDML Estimators

Computes a coefficient table with estimates, standard errors, z-values, and p-values for all ensemble types. Standard errors are based on a heteroskedasticity-robust sandwich variance; see vcov.ral for the HC0/HC1/HC3 formulas.

Usage

# S3 method for class 'ddml'
summary(object, type = "HC1", ...)

# S3 method for class 'summary.ddml'
print(x, digits = 3, ...)

Arguments

object

An object of class ddml.

type

Character. HC type ("HC0", "HC1", or "HC3"). Default "HC1".

...

Currently unused.

x

An object of class summary.ddml.

digits

Number of significant digits. Default 3.

Value

An object of class summary.ddml with:

coefficients

A 3-dimensional array (\(p \times 4 \times\) nensb) of estimates, standard errors, z-values, and p-values.

type

The HC type used.

nobs

Number of observations.

sample_folds

Number of cross-fitting folds.

ensemble_type

Ensemble type labels.

See also

vcov.ral

Other ddml inference: lincom()

Examples

# \donttest{
y = AE98[, "worked"]
D = AE98[, "morekids"]
X = AE98[, c("age","agefst","black","hisp","othrace")]
plm_fit = ddml_plm(y, D, X,
                learners = list(what = ols),
                sample_folds = 2, silent = TRUE)
summary(plm_fit)
#> DDML estimation: Partially Linear Model 
#> Obs: 5000   Folds: 2
#> 
#>             Estimate Std. Error z value Pr(>|z|)    
#> D1          -0.15376    0.01471  -10.45   <2e-16 ***
#> (Intercept) -0.00011    0.00690   -0.02     0.99    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
summary(plm_fit, type = "HC3")
#> DDML estimation: Partially Linear Model 
#> Obs: 5000   Folds: 2  SE: HC3
#> 
#>             Estimate Std. Error z value Pr(>|z|)    
#> D1          -0.15376    0.01472  -10.45   <2e-16 ***
#> (Intercept) -0.00011    0.00690   -0.02     0.99    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# }