hdCBPS: hdCBPS high dimensional CBPS method to parses the formula...
In CBPS: Covariate Balancing Propensity Score

Description Usage Arguments Value Author(s)

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.

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

`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.
`y`	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".

`ATT`	Average treatment effect on the treated.
`ATE`	Average treatment effect.
`s`	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