hdCBPS: hdCBPS high dimensional CBPS method to parses the formula object and passes the result to hdCBPS.fit, which calculates ATE using CBPS method in a high dimensional setting.

Description

hdCBPS high dimensional CBPS method to parses the formula object and passes the result to hdCBPS.fit, which calculates ATE using CBPS method in a high dimensional setting.

Usage

hdCBPS(
  formula,
  data,
  na.action,
  y,
  ATT = 0,
  iterations = 1000,
  method = "linear"
)

Arguments

formula

An object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted.

data

An optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which CBPS is called.

na.action

A function which indicates what should happen when the data contain NAs. The default is set by the na.action setting of options, and is na.fail if that is unset.

An outcome variable.

ATT

Option to calculate ATT

iterations

An optional parameter for the maximum number of iterations for the optimization. Default is 1000.

method

Choose among "linear", "binomial", and "possion".

Value

ATT

Average treatment effect on the treated.

ATE

Average treatment effect.

Standard Error.

fitted.values

The fitted propensity score

coefficients1

Coefficients for the treated propensity score

coefficients0

Coefficients for the untreated propensity score

model

The model frame