In recent years there has been a tremendous upsurge in research into SEMs, focusing on an increasing range of applications. This book provides an introduction to SEMs, and covers Bayesian approaches to analyzing them. It features a large number of real examples to illustrate the theory and explain computation techniques. The book is supported by a Website featuring computing code and data sets making it an excellent addition to the Wiley Series in Probability and Statistics.