Development of Introductory Software on Bayesian Inference Modeling for Stan and R

Abstract

Purpose of study: Stan is a new programming language used for Bayesian inference that implements the Hamiltonian Monte Carlo (HMC) algorithm. There is a high possibility that, going forward, this language will be widely adopted within the healthcare domain as well for research that makes use of Markov chain Monte Carlo (MCMC) methods. We have developed a new software, with the principle aim of helping healthcare researchers become acquainted with Bayesian inferences. This software is free and makes it simpler to run models written using Stan. Materials and methods: The current software “Fatsia” is an operation management tool or macro tool that controls data files, Stan files, Stan, and R. The core specifications for Fatsia are as follows: The operation windows were positioned in a manner that followed the procedure for running the MCMC modeling on Stan. Several MCMC models were prepared as templates, with the user able to directly run the template they selected, or to edit that template. Results and findings: The free software, Fatsia, that we developed met the above specifications. It could be operated via a graphical user interface (GUI), with the use of keyboard input outside of the necessary procedures, reduced to the smallest degree possible. When controlling Stan and R, Fatsia can export Stan files to R and commands R to execute MCMC methods on the R console. Conclusions: The usefulness of Fatsia was in streamlining the procedure for executing an MCMC using Stan. With Fatsia, we were able to run Stan MCMC models with the smallest possible amount of keyboard use. When compared with OpenBUGS or RStudio, the operation of Fatsia is easier, showing a high degree of utility. Hence, the implementation of more MCMC templates can be expected in the future.