Semi quantitative open source Bayesian models
What is it about?
This work builds on the previous 2 papers on open source Bayesian Models by us to describe a new method for creating composite models - data has multiple bins and we attempt to predict these instead of binary bins.
Why is it important?
We wanted to expand the scope of Bayesian models, make them more accessible to non-experts. But at the same time binary data may not be ideal when the underlying data is high quality dose response data, so an expansion of this approach was warranted. Multiple bins provides a semi-quantitative approach to prediction. Multiple Bayesian models essentially compete and the predicted bin is from the model with the highest score.
The following have contributed to this page: Dr Sean Ekins