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[Factor Score Path Analysis: An Alternative for SEM?](http://www.citeulike.org/user/guhjy/article/14660175)

[FSR](https://www.rdocumentation.org/packages/lavaan/versions/0.6-1.1161/topics/fsr)

lavaan is a free, open source R package for latent variable analysis. You can
use lavaan to estimate a large variety of multivariate statistical models,
including path analysis, confirmatory factor analysis, structural equation
modeling and growth curve models.

The lavaan package is developed to provide useRs, researchers and teachers a
free open-source, but commercial-quality package for latent variable modeling.
The long-term goal of lavaan is to implement all the state-of-the-art
capabilities that are currently available in commercial packages. However,
lavaan is still under development, and much work still needs to be done.

However, there are some settings in which SEM is still the best alternative. 
Unless additional restrictions are implemened, factor score regression methods only work
when there are at least three items per latent variable.
For the moment, the method of Croon also does not work for connected measurement models,
such as models with cross-loadings or correlated residual errors.
However, we are currently extending the method to be able to handle these kinds of models.
We also want to make some extensions to the inference of the model.
In future research, we want to use standard errors that are suitable for two-step estimation methods,
and we want to develop fit indices, so that the fit of the model can be evaluated,
just as in SEM. Finally, we also plan to implement the method in lavaan.

To get a first impression of how lavaan works in practice, consider the
following example of a SEM model (the Political Democracy Example from Bollen's 1989 book):

library(lavaan)

model <- '
   # latent variable definitions
     ind60 =~ x1 + x2 + x3
     dem60 =~ y1 + y2 + y3 + y4
     dem65 =~ y5 + y6 + y7 + y8
   # regressions
     dem60 ~ ind60
     dem65 ~ ind60 + dem60
   # residual covariances
     y1 ~~ y5
     y2 ~~ y4 + y6
     y3 ~~ y7
     y4 ~~ y8
     y6 ~~ y8
'
fit <- sem(model, data=PoliticalDemocracy)
summary(fit)

More information can be found on the website: http://lavaan.org