README.md

In Roche/descem: Discrete Event Simulation for Cost-Effectiveness Modelling

descem: Discrete Event Simulation for Cost-Effectiveness Modeling

Introduction

descem is a user-friendly package that facilitates the use of discrete event simulations without resource constraints for cost-effectiveness analysis. The package supports a flexible, practical approach to discrete event simulation while keeping an acceptable performance through the use of parallel computing.

The current version supports:

• Discrete event simulation models, Markov/semi-Markov models and hybrid models
• Seamlessly integrating data.frames and other objects into the model
• Delayed execution of the main inputs to facilitate readability of the model
• Debugging mode with a non-parallel engine to facilitate error detection
• Implementation of structural and parameter uncertainty
• Helper functions to facilitate drawing of time to events and the use of hazard ratios
• Performing cost-effectiveness and uncertainty analysis

It is recommended that the user checks the vignettes, first the simple Sick-Sicker-Dead model Sick-Sicker-Dead model and then the more complex model for early breast cancer. The markov example shows how to run a cohort Markov model while using the same modeling framework. Similarly, a simulation based Markov model could be run. Structural and parametric uncertainty are explored in the corresponding vignette. The IPD vignette shows how descem can be used when individual patient data is available.

Documentation

Have a look at the package home site for more details on documentation and specific tutorials.

For more details on the code, check our Github repository.

Installation

descem can the be installed directly from this repo via

# install.packages("devtools")
devtools::install_github("roche/descem", ref="main")

Citation

If you use descem, please contact the authors for the most up to date appropiate citation.

Roche/descem documentation built on July 27, 2022, 11:18 a.m.