Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata's sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning. A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.
Introduction to confirmatory factor analysis Introduction The "do not even think about it" approach The principal component factor analysis approach Alpha reliability for our nine-item scale Generating a factor score rather than a mean or summative score What can CFA add? Fitting a CFA model Interpreting and presenting CFA results Assessing goodness of fit A two-factor model Parceling Extensions and what is next Exercises Using the SEM Builder to run a CFA Using structural equation modeling for path models Introduction Path model terminology A substantive example of a path model Estimating a model with correlated residuals Auxiliary variables Testing equality of coefficients A cross-lagged panel design Moderation Nonrecursive models Exercises Using the SEM Builder to run path models Structural equation modeling Introduction The classic example of a structural equation model Equality constraints Programming constraints Structural model with formative indicators Exercises Latent growth curves Discovering growth curves A simple growth curve model Identifying a growth curve model An example of a linear latent growth curve How can we add time-invariant covariates to our model? Explaining the random effects-time-varying covariates Constraining variances of error terms to be equal (optional) Exercises Group comparisons Interaction as a traditional approach to multiple-group comparisons The range of applications of Stata's multiple-group comparisons with sem A measurement model application Multiple-group path analysis Multiple-group comparisons of structural equation models Exercises Epilogue-what now? What is next? The graphical user interface Introduction Menus for Windows, Unix, and Mac Designing a structural equation model Drawing an SEM model Fitting a structural equation model Postestimation commands Clearing preferences and restoring the defaults B Entering data from summary statistics
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