References

Literature underpinning CausalDynamics.jl. BibTeX keys match the CDCS book references.bib where possible. For estimation (LMTP, mediation TMLE, Super Learner), see also CausalTargeted.jl references.

Structural causality and identification

Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. — key pearl2009causality
Pearl, J. (2018). The Book of Why. Basic Books. — key pearl2018bookofwhy
Shpitser, I., & Pearl, J. (2006). Identification of joint interventional distributions in recursive semi-Markovian causal models. In AAAI. — key shpitser2006identification
Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, Prediction, and Search (2nd ed.). MIT Press. — key spirtes2000causation
Peters, J., Janzing, D., & Schölkopf, B. (2017). Elements of Causal Inference. MIT Press. — key peters2017elements
Bareinboim, E., & Pearl, J. (2016). Causal inference and the data-fusion problem. Proceedings of the National Academy of Sciences, 113(27), 7345–7352. — key bareinboim2016causal
Imbens, G. W., & Rubin, D. B. (2015). Causal Inference for Statistics, Social, and Biomedical Sciences. Cambridge University Press. — key imbens2015causal

g-methods and longitudinal confounding

Robins, J. (1986). A new approach to causal inference in mortality studies with a sustained exposure period. Mathematical Modelling, 7, 1393–1512. — key robins1986new
Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560. — key robins2000marginal
Hernán, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. — key hernan2020causal

Time-indexed / dynamical graphs

Unrolled lag DAGs (TemporalDAGSpec, unroll_temporal_dag, TemporalEffectQuery) apply standard backdoor criteria on an expanded static graph. Conceptual links:

Pearl (2009), Ch. on dynamic models / time-indexed SCMs
Discrete-time CDMs in the CDCS book (Ch. 28)
Estimation of time-indexed MTP effects: Díaz et al. (2023), JASA — key diaz2023lmtp (implemented in CausalTargeted)

Mediation identification (structural)

Pearl, J. (2001). Direct and indirect effects. In UAI. — key pearl2001direct
Robins, J. M., & Greenland, S. (1992). Identifiability and exchangeability for direct and indirect effects. Epidemiology. — key robins1992estimation
Avin, C., Shpitser, I., & Pearl, J. (2005). Identifiability of path-specific effects. In IJCAI. — key avin2005identifiability
VanderWeele, T. J. (2015). Explanation in Causal Inference. Oxford University Press. — key vanderweele2015explanation

Discovery (optional Associations.jl bridge)

Spirtes et al. (2000) — PC and constraint-based search
Chickering, D. M. (2002). Optimal structure identification with greedy search. JMLR. — key chickering2002optimal
Runge, J., et al. (2019). Detecting and quantifying causal associations in large nonlinear time series datasets. Science Advances. — key runge2019detecting

Discovery outputs feed sensitivity comparisons in CausalTargeted (discovery_adjustment_sensitivity); they must not silently replace a user DAG.

Graphs.jl — graph data structures
CausalInference.jl — d-separation / backdoor façades used internally
CausalTargeted.jl — LMTP / mediation estimation consuming IdentificationResult
DAGMakie.jl — DAG visualisation
Associations.jl — optional discovery bridge
ModelingToolkit.jl / Symbolics.jl — symbolic modelling (SciML integration docs)