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Print Methods for Treatment Effect Estimators.

Source: R/ddml_fpliv.R, R/ddml_pliv.R, R/ddml_plm.R
print.summary.ddml_plm.Rd

Print methods for treatment effect estimators.

Usage

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

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

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

Arguments

x

An object of class summary.ddml_plm, summary.ddml_pliv, and summary.ddml_fpliv, as returned by summary.ddml_plm(), summary.ddml_pliv(), and summary.ddml_fpliv(), respectively.

digits

Number of significant digits used for priniting.

...

Currently unused.

Value

NULL.

Examples

# Construct variables from the included Angrist & Evans (1998) data
y = AE98[, "worked"]
D = AE98[, "morekids"]
X = AE98[, c("age","agefst","black","hisp","othrace","educ")]

# Estimate the partially linear model using a single base learner, ridge.
plm_fit <- ddml_plm(y, D, X,
                    learners = list(what = mdl_glmnet,
                                    args = list(alpha = 0)),
                    sample_folds = 2,
                    silent = TRUE)
summary(plm_fit)
#> PLM estimation results: 
#>  
#> , , single base learner
#> 
#>              Estimate Std. Error  t value Pr(>|t|)
#> (Intercept)  0.000177    0.00688   0.0257 9.79e-01
#> D_r         -0.147605    0.01473 -10.0224 1.21e-23
#>