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| Publisher: | Stata Press |
| Copyright: | 2025 |
| ISBN-13: | 978-1-59718-443-4 |
| Pages: | 680 |
Suggested citation:
StataCorp. 2025. Stata 19 Structural Equation Modeling Reference Manual. College Station, TX: Stata Press.
Discovering Structural Equation Modeling Using Stata, Revised Edition
Alan C. Acock
Structural equation modeling using Stata training course
| Acknowledgments | |
| Intro 1 | Introduction |
| Intro 2 | Learning the language: Path diagrams and command language |
| Intro 3 | Learning the language: Factor-variable notation (gsem only) |
| Intro 4 | Substantive concepts |
| Intro 5 | Tour of models |
| Intro 6 | Comparing groups |
| Intro 7 | Postestimation tests and predictions |
| Intro 8 | Robust and clustered standard errors |
| Intro 9 | Standard errors, the full story |
| Intro 10 | Fitting models with survey data |
| Intro 11 | Fitting models with summary statistics data (sem only) |
| Intro 12 | Convergence problems and how to solve them |
| Builder | SEM Builder |
| Builder, generalized | SEM Builder for generalized models |
| estat eform | Display exponentiated coefficients |
| estat eqgof | Equation-level goodness-of-fit statistics |
| estat eqtest | Equation-level test that all coefficients are zero |
| estat framework | Display estimation results in modeling framework |
| estat ggof | Group-level goodness-of-fit statistics |
| estat ginvariant | Tests for invariance of parameters across groups |
| estat gof | Goodness-of-fit statistics |
| estat lcgof | Latent class goodness-of-fit statistics |
| estat lcmean | Latent class marginal means |
| estat lcprob | Latent class marginal probabilities |
| estat mindices | Modification indices |
| estat residuals | Display mean and covariance residuals |
| estat scoretests | Score tests |
| estat sd | Display variance components as standard deviations and correlations |
| estat stable | Check stability of nonrecursive system |
| estat stdize | Test standardized parameters |
| estat summarize | Report summary statistics for estimation sample |
| estat teffects | Decomposition of effects into total, direct, and indirect |
| Example 1 | Single-factor measurement model |
| Example 2 | Creating a dataset from published covariances |
| Example 3 | Two-factor measurement model |
| Example 4 | Goodness-of-fit statistics |
| Example 5 | Modification indices |
| Example 6 | Linear regression |
| Example 7 | Nonrecursive structural model |
| Example 8 | Testing that coefficients are equal, and constraining them |
| Example 9 | Structural model with measurement component |
| Example 10 | MIMIC model |
| Example 11 | estat framework |
| Example 12 | Seemingly unrelated regression |
| Example 13 | Equation-level Wald test |
| Example 14 | Predicted values |
| Example 15 | Higher-order CFA |
| Example 16 | Correlation |
| Example 17 | Correlated uniqueness model |
| Example 18 | Latent growth model |
| Example 19 | Creating multiple-group summary statistics data |
| Example 20 | Two-factor measurement model by group |
| Example 21 | Group-level goodness of fit |
| Example 22 | Testing parameter equality across groups |
| Example 23 | Specifying parameter constraints across groups |
| Example 24 | Reliability |
| Example 25 | Creating summary statistics data from raw data |
| Example 26 | Fitting a model with data missing at random |
| Example 27g | Single-factor measurement model (generalized response) |
| Example 28g | One-parameter logistic IRT (Rasch) model |
| Example 29g | Two-parameter logistic IRT model |
| Example 30g | Two-level measurement model (multilevel, generalized response) |
| Example 31g | Two-factor measurement model (generalized response) |
| Example 32g | Full structural equation model (generalized response) |
| Example 33g | Logistic regression |
| Example 34g | Combined models (generalized responses) |
| Example 35g | Ordered probit and ordered logit |
| Example 36g | MIMIC model (generalized response) |
| Example 37g | Multinomial logistic regression |
| Example 38g | Random-intercept and random-slope models (multilevel) |
| Example 39g | Three-level model (multilevel, generalized response) |
| Example 40g | Crossed models (multilevel) |
| Example 41g | Two-level multinomial logistic regression (multilevel) |
| Example 42g | One- and two-level mediation models (multilevel) |
| Example 43g | Tobit regression |
| Example 44g | Interval regression |
| Example 45g | Heckman selection model |
| Example 46g | Endogenous treatment-effects model |
| Example 47g | Exponential survival model |
| Example 48g | Loglogistic survival model with censored and truncated data |
| Example 49g | Multiple-group Weibull survival model |
| Example 50g | Latent class model |
| Example 51g | Latent class goodness-of-fit statistics |
| Example 52g | Latent profile model |
| Example 53g | Finite mixture Poisson regression |
| Example 54g | Finite mixture Poisson regression, multiple responses |
| gsem | Generalized structural equation model estimation command |
| gsem estimation options | Options affecting estimation |
| gsem family-and-link options | Family-and-link options |
| gsem group options | Fitting models on different groups |
| gsem lclass options | Fitting models with latent classes |
| gsem model description options | Model description options |
| gsem path notation extensions | Command syntax for path diagrams |
| gsem postestimation | Postestimation tools for gsem |
| gsem reporting options | Options affecting reporting of results |
| lcstats | Latent class model-comparison statistics |
| lincom | Linear combinations of parameters |
| lrtest | Likelihood-ratio test of linear hypothesis |
| Methods and formulas for gsem | Methods and formulas for gsem |
| Methods and formulas for sem | Methods and formulas for sem |
| nlcom | Nonlinear combinations of parameters |
| predict after gsem | Generalized linear predictions, etc. |
| predict after sem | Factor scores, linear predictions, etc. |
| sem | Structural equation model estimation command |
| sem and gsem option constraints( ) | Specifying constraints |
| sem and gsem option covstructure( ) | Specifying covariance restrictions |
| sem and gsem option from( ) | Specifying starting values |
| sem and gsem option reliability( ) | Fraction of variance not due to measurement error |
| sem and gsem path notation | Command syntax for path diagrams |
| sem and gsem syntax options | Options affecting interpretation of syntax |
| sem estimation options | Options affecting estimation |
| sem group options | Fitting models on different groups |
| sem model description options | Model description options |
| sem option method( ) | Specifying method and calculation of VCE |
| sem option noxconditional | Computing means, etc. of observed exogenous variables |
| sem option select( ) | Using sem with summary statistics data |
| sem path notation extensions | Command syntax for path diagrams |
| sem postestimation | Postestimation tools for sem |
| sem reporting options | Options affecting reporting of results |
| sem ssd options | Options for use with summary statistics data |
| ssd | Making summary statistics data (sem only) |
| test | Wald test of linear hypotheses |
| testnl | Wald test of nonlinear hypotheses |
| Glossary | |
| Combined author index | |
| Combined subject index | |
