estimate_ps: Estimate propensity score
In PLUCR: Policy Learning Under Constraint

estimate_ps

R Documentation

Estimate propensity score

This function trains the propensity score models using SuperLearner, applying cross-validation to compute out-of-fold estimates.

estimate_ps(
  A,
  X,
  folds,
  SL.library = c("SL.glm", "SL.mean"),
  V = 2L,
  threshold = 0.01
)

`A`	A binary vector or matrix of length n indicating treatment assignment (0 or 1).
`X`	A matrix or data frame of covariates of size n x d (input data in `⁠[0,1]⁠`).
`folds`	A list of cross-validation folds (e.g., a list of indices for each fold).
`SL.library`	Vector of libraries for training SuperLearner (c("SL.glm", "SL.mean") by default).
`V`	Number of folds inside the SuperLearner (2L by default).
`threshold`	A numeric scalar that sets the minimum allowed value for upper and lower bound estimations (1e-2 by default). Constrains estimation to `⁠[threshold, 1 - threshold]⁠`.