This tutorial is a reasonably self-contained tutorial and documentation source about trasitioning to bayesian analysis from traditional first order estimation techniques for nonlinear-mixed-effects modeling. The overarching objective is to provide a resource for some of the additional complexity that bayesian analysis suggests/requires (mu-modeling, additional estimation tuning, etc) and to compare output under various scenarios to that of FOCE-based estimation.
As a secondary objective, this project should serve as a case study to managing a collaborative project using git, github and other ‘modern’ tooling for reproducible science. For contribution guidelines, see the CONTRIBUTING section below.
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States License.