Changes in version 0.1.0                        

Initial release of the marbounds package for bounding causal effects
under mixed informative and non-informative missingness.

Features

  - mar_bounds() - Main function for computing bounds on causal effects
  - Support for multiple estimands: ATE, composite ATE (Ψ₁), separable
    direct effect (Ψ₂)
  - Multiple assumption types:
      - General bounds (no assumptions)
      - Bounded proportion of informative missingness (δ)
      - Monotonicity (positive/negative)
      - Bounded outcome risk (τ)
      - Point identification under known sensitivity parameters
  - SuperLearner integration for nuisance parameter estimation with
    V-fold cross-fitting
  - Multiplier bootstrap for simultaneous inference over parameter grids
  - Influence function-based estimators with asymptotic standard errors

Reference

Rubinstein, M., Agniel, D., Han, L., Horvitz-Lennon, M., & Normand,
S.-L. (2026). Bounding causal effects with an unknown mixture of
informative and non-informative missingness. Journal of Causal Inference
(Accepted). https://arxiv.org/pdf/2411.16902