Wrapper for Double machine learning data-backend initialization from data.frame. — double_ml_data_from_data

Initalization of DoubleMLData from data.frame.

Usage

double_ml_data_from_data_frame(
  df,
  x_cols = NULL,
  y_col = NULL,
  d_cols = NULL,
  z_cols = NULL,
  s_col = NULL,
  cluster_cols = NULL,
  use_other_treat_as_covariate = TRUE
)

Arguments

df: (data.frame())
Data object.
x_cols: (NULL, character())
The covariates. If NULL, all variables (columns of data) which are neither specified as outcome variable y_col, nor as treatment variables d_cols, nor as instrumental variables z_cols are used as covariates. Default is NULL.
y_col: (character(1))
The outcome variable.
d_cols: (character())
The treatment variable(s).
z_cols: (NULL, character())
The instrumental variables. Default is NULL.
s_col: (NULL, character())
The score or selection variable (only relevant/used for SSM Estimators). Default is NULL.
cluster_cols: (NULL, character())
The cluster variables. Default is NULL.
use_other_treat_as_covariate: (logical(1))
Indicates whether in the multiple-treatment case the other treatment variables should be added as covariates. Default is TRUE.

Value

Creates a new instance of class DoubleMLData.

Examples

df = make_plr_CCDDHNR2018(return_type = "data.frame")
x_names = names(df)[grepl("X", names(df))]
obj_dml_data = double_ml_data_from_data_frame(
  df = df, x_cols = x_names,
  y_col = "y", d_cols = "d")
# Input: Data frame, Output: DoubleMLData object