LISREL - SIMPLIS, LISREL and PRELIS Examples

For Multilevel, Complex Survey, MGLIM and MVA examples, please see the LISREL - Multilevel, Complex Survey, MGLIM and MVA examples page.

See also our Support & Documentation page.

LISREL can be used to fit:

• measurement models,

• structural equation models based on continuous or ordinal data,

• multilevel models for continuous and categorical data using a number of link functions,

• generalized linear models based on complex survey data.

Additional statistical analyses than can be performed include, to name a few:

• exploratory factor analysis (EFA),

• multivariate analysis of variance (MANOVA),

• logistic and probit regression,

• censored regression,

• survival analysis.

To facilitate learning how to use LISREL or teaching with LISREL, an extensive collection of completely worked examples is available for download. Please select the topic of interest from the list below.

To download the entire set of examples, click here.

To see an example of the new HTML output available for selected models in LISREL 12, click here. For more on new features in LISREL 12, please see New Features.

Preview the example by clicking on each of the topics below, or download the entire example (PDF, data and syntax files) by clicking on the link in parentheses after the topic name. 

Getting started:

• Getting descriptive statistics (complete example)

• Using existing LISREL syntax files (complete example)

• Using existing LISREL project files (complete example)

• Using existing SIMPLIS syntax files (complete example)

• Using existing SIMPLIS project files (complete example)

• An introduction to SEM for single groups (complete example)

New 16 character examples:

• Adaptive quadrature analysis of political efficacy data (complete example)

• FIML and missing data: assessment of invariance (complete example)

• Reading labels from an external file (complete example)

• Analysis of reader reliability (complete example)

• Multilevel SEM analysis with structured means (complete example)

• Using a polychoric correlation matrix with ordinal variables (complete example)

• Multiple group analysis with SIMPLIS (complete example)

Two-stage multiple imputation (MI2S) examples:

• Two-stage multiple imputation SEM for political efficacy data (complete example)

• Two-stage multiple imputation SEM for morality data (complete example)

• Two-stage multiple imputation SEM for panel data (complete example)

• Two-stage multiple imputation SEM using panel data

• Two-stage multiple imputation SEM using prostate cancer data

• Two-stage multiple imputation SEM using student data

• Two-stage multiple imputation SEM using simulated data for girls

SIMPLIS examples:

Regression models:

• Regression of GNP (complete example)

• Bivariate regression (complete example)

• Regression models with latent variables: regression of Verbal7 on Verbal5 (complete example)

• Regression models with latent variables: Head Start summer program (complete example)

Structural Equation Models without latent variables:

• SEM for directly observed variables (complete example)

Structural Equation Models with latent variables:

• Measurement models: Ability and aspiration (complete example)

• Path analysis with latent variables: stability of alienation (complete example)

• Path analysis with latent variables: performance and satisfaction (complete example)

• Non-recursive system: peer influences on ambition (complete example)

• Estimation of means of latent variables: mean difference in verbal ability (complete example)

• Estimation of means of latent variables: nine psychological variables with factor means (complete example)

• Structural equation model for work ethics data (complete example)

• Path diagrams (complete example)

• Confidence interval estimates for work ethic data (complete example)

Factor analysis and principal component analysis:

• A factor analysis model (complete example)

• Exploratory factor analysis (complete example)

• Confirmatory Factor Analysis with nine psychological variables (complete example)

• CFA for continuous variables without missing values (complete example)

• Confirmatory factor analysis of ordinal data: example 1 (complete example)

• Confirmatory factor analysis of ordinal data: example 2 (complete example)

• Standard errors for standardized solutions using student data (complete example)

Multiple group examples:

• Multi sample analyses using path diagrams (complete example)

• Multi-group analysis: equality of factor structures (complete example)

• Multi-group analysis: parental socioeconomic characteristics (complete example)

• Multi-group analysis: equal regressions (complete example)

Ordinal data analysis:

• Analysis of ordinal variables: panel model for political efficacy (complete example)

• A structural equation model for ordinal data (complete example)

• Ordinal variables without missing values (complete example)

Two-Stage Least Squares examples:

• Two-Stage Least Squares: Tintner’s meat market model (complete example)

Observational residuals examples:

• Latent variable scores (complete example)

• Latent variable scores and calculating residuals (complete example)

• Estimating residuals using the Kenny-Judd data (complete example)

Missing data examples:

• Latent curve model for continuous variables with missing values (complete example)

• Assessment of invariance (complete example)

• The assessment of validity of constructs (complete example)

• Exploring smoking habits of youth using NLSY79 data (complete example)

• Use of alcohol and tobacco by youth: NLSY79 data (complete example)

Additional SIMPLIS examples:

• SEMS using LISREL output (complete example)

• Fit statistics (complete example)

LISREL Examples:

Anova and regression:

• Analysis of variance and covariance (complete example)

• Stepwise regression (complete example)

Structural Equation Models without latent variables:

• Estimating the disattenuated correlation (complete example)

• Path analysis (complete example)

• Analysis based on covariance matrices: Example 1 (complete example)

• Analysis based on covariance matrices: Example 2 (complete example)

• Variance and covariance components (complete example)

Structural Equation Models with latent variables:

• Congeneric measures: multi factor model (complete example)

• Measurement error in regression (complete example)

• Path analysis with latent variables (complete example)

• Path analysis with latent variables: example 2 (complete example)

• Two-wave models (complete example)

• Two-wave models (complete example)

• Analysis based on covariance matrices: Example 3 (complete example)

• Subjective and objective social class (complete example)

• Latent variable models with interaction and non-linear relationships (complete example)

• Hypothesis testing and power calculation (complete example)

• Chi-squares in LISREL (complete example)

• Use of constraints in a LISREL model (complete example)

Factor analysis and Principal Component analysis:

• Confirmatory factor analysis (complete example)

• Second order factor analysis (complete example)

• Confirmatory factor analysis for school data (complete example)

• Confirmatory Factor Analysis for continuous variables without missing values (complete example)

• Principal components analysis of meteorological data (complete example)

• Factor analysis of dichotomous variables (complete example)

• Standard errors for standardized solutions using ability test data (complete example)

MIMIC and Simplex models:

• MIMIC models (complete example)

• Simplex models (complete example)

• Estimating correlation structures with WLS (complete example)

Mean structures examples:

• Mean structures: Example 1 (complete example)

• Mean structures: Example 2 (complete example)

Multiple group analysis:

• An introduction to SEM for multiple group analysis (complete example)

Missing data examples:

• Incomplete data (complete example)

• Single-group analysis with missing data (complete example)

• Multiple group analysis with missing data (complete example)

• Multiple imputation and FIML (complete example)

Latent curve examples:

• Growth curves (complete example)

Ordinal data analysis:

• Analysis of ordinal variables (complete example)

• Analysis of ordinal variables: example 2 (complete example)

Two-stage least squares:

• Econometric models (complete example)

Additional LISREL examples:

• Problems with analysis of correlation matrices (complete example)

• A model for tests that differ in length only (complete example)

PRELIS examples:

Exploring data and basic statistics:

• Data screening and summarization (complete example)

• Naming variables and categories of variables (complete example)

• Logarithmic transformations and recoding of variables (complete example)

• Exploratory analysis of fitness data (complete example)

• Exploratory analysis of political data (complete example)

• Data manipulation and bivariate plots (complete example)

• Normalizing variables (complete example)

• Regression (complete example)

• Estimated regressions (complete example)

• Compute matrix polyserial and polychoric correlations (complete example)

• Polychoric correlation matrix with all variables ordinal (MA = PM) (complete example)

• Tetrachoric correlations with asymptotic variance estimated from grouped data (complete example)

• Estimating asymptotic variances and covariances (MA=CM) (complete example)

• Estimating asymptotic variances and covariances (MA = KM) (complete example)

• Estimating asymptotic variances and covariances (MA=PM) (complete example)

• Test of univariate and multivariate normality (complete example)

• Threshold estimates (complete example)

• Latent variable models with interaction and non-linear relationships (complete example)

• Normal scores (complete example)

• Homogeneity tests for categorical variables (complete example)

• Multivariate multinomial probit regressions (complete example)

Imputation and bootstrap examples:

• Bootstrap samples (complete example)

• Monte Carlo studies

• Multiple imputation (complete example)

• Bootstrap estimates (complete example)

• Monte Carlo: generating normal variables (complete example)

• Monte Carlo: generating non-normal variables (complete example)

Factor analysis and Principal Components analysis:

• Exploratory factor analysis (complete example)

Ordinal data analysis:

• Preliminary analysis of ordinal data (complete example)

Two-Stage Least Squares examples:

• Two stage least squares (complete example)

• Two-Stage Least Squares: Klein’s model of the US economy (complete example)

Censored data:

• Notes by K G Jöreskog on censored variables and censored regression (complete example)

• Censored regression (complete example)