Corpus ID: 210859128

Cohort state-transition models in R: From conceptualization to implementation.

@article{AlaridEscudero2020CohortSM,
  title={Cohort state-transition models in R: From conceptualization to implementation.},
  author={Fernando Alarid-Escudero and Eline M. Krijkamp and Eva A. Enns and M. G. Myriam Hunink and Petros Pechlivanoglou and Hawre J Jalal},
  journal={arXiv: Applications},
  year={2020}
}
  • Fernando Alarid-Escudero, Eline M. Krijkamp, +3 authors Hawre J Jalal
  • Published 2020
  • Mathematics, Biology
  • arXiv: Applications
  • Decision models can synthesize evidence from different sources to provide estimates of long-term consequences of a decision with uncertainty. Cohort state-transition models (cSTM) are decision models commonly used in medical decision making because they can simulate hypothetical cohorts' transitions across various health states over time. This tutorial shows how to conceptualize cSTMs in a programming language environment and shows examples of their implementation in R. We illustrate their use… CONTINUE READING

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 38 REFERENCES

    Cost-Effectiveness Analysis of Treatments for Chronic Disease: Using R to Incorporate Time Dependency of Treatment Response

    Continuous-Time Semi-Markov Models in Health Economic Decision Making

    • Qi Cao, Erik Buskens, +3 authors Douwe Postmus
    • Sociology, Medicine
    • Medical decision making : an international journal of the Society for Medical Decision Making
    • 2016

    State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--3.

    A Mathematical Approach for Evaluating Markov Models in Continuous Time without Discrete-Event Simulation

    Markov Models in Medical Decision Making

    Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial

    Identification of a Multistate Continuous-Time Nonhomogeneous Markov Chain Model for Patients with Decreased Renal Function