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cff-version: 1.2.0
message: 'To cite package "CausalState" in publications use:'
type: software
license: AGPL-3.0-only
title: 'CausalState: Causal Inference in a Longitudinal Transitioning State Environment'
version: 0.10.2
doi: 10.32614/CRAN.package.CausalState
abstract: Implements Sequential Doubly Robust (SDR) and infinite-dimensional Targeted
  Maximum Likelihood (iTMLE) estimators for longitudinal modified treatment policies
  in settings with transitioning states, such as ICU, ward, or emergency department
  care episodes. Treatment is permitted in active states and becomes structurally
  inapplicable after a state transition (e.g. discharge or death). Supports asymmetric
  g- and Q-model regularisation, k-fold cross-fitting, and pluggable SuperLearner
  ensembles. Includes specialised SuperLearner wrappers (SL.tgt.* and SL.tmle_* families)
  for the iTMLE targeting step, which pass the logit offset as a covariate column
  to preserve correct subsetting during SuperLearner cross-validation. Methods based
  on Diaz et al. (2021) <https://doi.org/10.1080/01621459.2021.1955691> and Luedtke
  et al. (2017) <https://doi.org/10.48550/arXiv.1705.02459>.
authors:
- family-names: Blank
  given-names: Sebastiaan
  email: sebastiaan.blank@mail.com
  orcid: https://orcid.org/0000-0001-9115-2138
repository: https://sebastiaan-blank.r-universe.dev
repository-code: https://github.com/sebastiaan-blank/CausalState
commit: 45ab7facea83e319c8e7b95ecbf772939a0afa7d
url: https://github.com/sebastiaan-blank/CausalState
date-released: '2026-10-05'
contact:
- family-names: Blank
  given-names: Sebastiaan
  email: sebastiaan.blank@mail.com
  orcid: https://orcid.org/0000-0001-9115-2138