SEM and NPMR are actually quite different. To name a few differences:
- SEM is based on a linear model; NPMR assumes no particular shape of relationships. (SEM works on covariance matrices while NPMR uses multidimensional smoothers.)
- Interactions must be modeled explicity with SEM but are implicit and automatic with NPMR.
- SEM requires a structured hypothesis on how the variables are interrelated while NPMR starts with no assumed structure Instead, NPMR uses the data to expose relationships of the form y = f(x1, x2, ...) where f is an unspecified smooth function. SEM users usually have much more complicated structures to evaluate.
Hope this helps.
-Bruce McCune