print.summary.ddml_plm: Print Methods for Treatment Effect Estimators.

In ddml: Double/Debiased Machine Learning

Print Methods for Treatment Effect Estimators.

Description

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)

ddml documentation built on Oct. 3, 2024, 1:13 a.m.