A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example

This GitHub repository provides the code of the tutorial on how to implement time-dependent cohort state-transition models (cSTMs) in R using a cost-effectiveness analysis (CEA) example, explained in the following manuscript:

• Alarid-Escudero F, Krijkamp EM, Enns EA, Yang A, Hunink MGM, Pechlivanoglou P, Jalal H. A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example. arXiv:2108.13552v1. 2021:1-37.

The release that accompanies the published article has been archived in zenodo.

The R folder includes two different scripts corresponding to functions used to synthesize cSTMs outputs and conduct several sensitivity analyses:

• Funtions.R: Functions to generate epidemiological measures from time-dependent cSTMs.

• Functions_cSTM_time_dep_simulation.R: These functions wrap the simulation-time dependent cSTM, compute CEA measures, and generate probabilistic sensitivity analysis (PSA) input datasets.

• Functions_cSTM_time_dep_state_residence.R: These functions wrap the state-residence time dependent cSTM, compute CEA measures, and generate probabilistic sensitivity analysis (PSA) input datasets.

GitHub repository and the accompanying manuscript can be downloaded here.