Introduction
Structural equational modeling is a widely used method ins reserach, mainly in the social sciences. My reserach interest is in alternative approches to this field, aiming at he following goals:
  • Estimate models with non-linear relations
  • Estimate models with non-normal latent and manifest variables
  • Estimate values of latent vaiables
  • Check assumptions of standard SEM such as indendency of error variables
  • Allow implicative relations in models

Polynomial SEM
Extending the traditional approach to polynomial models seems to be simpler than published approaches.

  • Polynomial SEM based on Isserlis' theorem. This Preprint explains the technique and contains links to implementations.

Case based SEM
A very general approach is possible by estimating the equations case by case.