My problem with books like this is that they have almost no connection to why Bayesian statistics is successful: Bayesian statistics provides a unified recipe to tackle complex data analysis problems. Arguably the only known unified recipe.
The Bayesian book I want should emphasize how Bayes is a recipe for studying complex problems and teach a broad range of model ingredients. Learning Bayesian statistics is about becoming fluent in describing scientific problems in probabilistic language. This requires knowing how to express and compose traditional models and build new ones based on first principles.
An unfortunate reality is that you still need to know computational methods too, but that should change soon enough.
The Bayesian book I want should emphasize how Bayes is a recipe for studying complex problems and teach a broad range of model ingredients. Learning Bayesian statistics is about becoming fluent in describing scientific problems in probabilistic language. This requires knowing how to express and compose traditional models and build new ones based on first principles.
An unfortunate reality is that you still need to know computational methods too, but that should change soon enough.