About the Content: The information on this site may be useful for folks from all scientific disciplines. That said, my background is in the natural sciences and the great majority of information online about SEM is from the social and economic sciences, so my secondary purpose is to provide illustrations that support natural science applications.
A Bit About Organization: Since this is meant to be a "how to" website, I present tutorials and then have available the code for several different analysis platforms. At present, I provide code for three platforms.
1- Amos (easy to use GUI-based software designed for teaching SEM). This is best suited for scientists who want to get up and running with SEM quickly.
2- Lavaan (a package of the R software). For those using R, this is emerging as a powerful package for matrix-based SEM.
3- Bayesian SEM (winBUGS and R2BUGS programming for customized model specification using Markov chain Monte Carlo methods). The Bayesian approach can provide extreme versatility in model specification. However, the business of model evaluation is not automated in the Bayesian approach, which means Bayesian SEM requires much more time to use properly.