i'm looking for a book with a combination of easy to understand theory and some examples with statistical softwares about bayesian structural equation modeling.
Nautilus has an accessible discussion, a bit broad maybe. It was picked up by Art and Letters Daily and the address is: http://nautil.us/issue/74/networks/the-flawed-reasoning-behind-the-replication-crisis. It sounds like you will need some trial and error, and good luck with that.
It may be useful to begin with MCMC estimation in a standard regression model - I have a detailed ( and it is to be hoped , gentle ) and applied example in this book, so you can your head around priors , posteriors and traces in the simplest possible case of a mean cast as a regression model:
Book Developing multilevel models for analysing contextuality, he...