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Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial.
Eline M Krijkamp1, Fernando Alarid-Escudero2, Eva A Enns2
1Erasmus MC, Epidemiology Department, Rotterdam, The Netherlands.
Summary
This tutorial provides a guide for building health decision microsimulation models in R. It offers efficient, reproducible code for transparent and adaptable model development.
Area of Science:
- Health economics and outcomes research
- Computational modeling and simulation
- Biostatistics and data science
Background:
- Microsimulation models are increasingly used in health decision modeling.
- These models are computationally intensive, driving the adoption of programming languages.
- R is recognized for its efficiency and transparency in decision modeling.
Purpose of the Study:
- To provide a step-by-step guide for implementing microsimulation models in R.
- To offer flexible, generic R code adaptable for various decision problems.
- To demonstrate an efficient microsimulation approach using vectorization.
Main Methods:
- Development of a tutorial with generic R code.
- Illustration using a hypothetical, transferable decision problem.
- Guidance on extending code for complex model structures.
Main Results:
- A clear, step-by-step implementation guide for R microsimulation models.
- Flexible and adaptable R code provided.
- Demonstration of efficient microsimulation through vectorization.
Conclusions:
- R offers an efficient platform for developing transparent and reproducible microsimulation models.
- The provided guide and code facilitate the implementation of complex health decision models.
- This work addresses the need for clear guidance in applying R for microsimulation.
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