LISREL and AMOS have been the two most commonly used software to estimate SEM. Professor John Fox authored an R package, sem, which allows R users to estimate the basic SEM. Professor Fox used Wheaton, Muthén, Alwin, and Summers’s (1977) panel data to illustrate estimation of SEM. Stata 12 also illustrates SEM using the same data set.
Stata 12, according to Stata's website, supports the following in SEM:
- Use GUI or command language to specify model.
- Standardized and unstandardized results.
- Direct and indirect effects.
- Goodness-of-fit statistics.
- Tests for omitted paths and tests of model simplification including modification indices, score tests, and Wald tests.
- Predicted values and factor scores.
- Linear and nonlinear (1) tests of estimated parameters and (2) combinations of estimated parameters with CIs.
- Estimation across groups is as easy as adding group(sex) to the command. Test for group invariance. Easily add or relax constraints across groups.
- SEMs may be fitted using raw or summary statistics data.
- Maximum likelihood (ML) and asymptotic distribution free (ADF) estimation. ADF is also known as generalized method of moments (GMM). Missing at random (MAR) data supported via FIML.
- Robust estimate of standard errors and standard errors for clustered samples available.
- Support for survey data including sampling weights, stratification and poststratification, and clustered sampling at one or more levels.
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