LISREL Examples

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 are available for download. Please select the topic of interest from the list below.

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. 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.

• Getting started
• New 16 character examples
• New MI2S examples
• SIMPLIS examples
• LISREL Examples
• PRELIS examples
• Multilevel data examples
• Complex survey data examples
• Multilevel Generalized Linear Modeling examples
• Examples from Multivariate Analysis with LISREL
• Ordinal data analysis in LISREL

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 alchol 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)

Multilevel data examples:

Linear models:

• Using design weights   (complete example)
• Analysis of 2-level repeated measures data (complete example)
• Analysis of air traffic control data (complete example)
• Multivariate analysis of educational data (complete example)
• Multilevel CFA models   (complete example)
• 3-level analysis of health expenditure data   (complete example)
• 3-level analysis of CPC survey data (complete example)
• 3-level analysis of simulated data   (complete example)
• 3-level saturated model for simulated data   (complete example)
• 4-level model for assessment data   (complete example)
• Five-level model for simulated data (complete example)

Non-linear models:

• Description of nonlinear multilevel models available
• 2-level nonlinear multilevel model   (complete example)
• Logistic curves for the weight gain of cows (complete example)
• Logistic curve for simulated data (complete example)
• Exponential curve for simulated data (complete example)
• Gompertz curve for simulated data (complete example)
• Logistic curve for simulated data (complete example)
• Exponential curve for simulated data (complete example)
• Monomolecular model for simulated data (complete example)
• Nonlinear growth curve for the height of males (complete example)
• Nonlinear growth curve for height of females (complete example)
• Nonlinear growth curves for Japanese girls (complete example)
• Growth curve for weight of chicks (complete example)
• A growth curve for the weighs of male mice (complete example)
• Nonlinear curves for the weights of male and female mice (complete example)
• Monomolecular curve for the Vonesh data (complete example)
• Monomolecular curve for nitrogen washout data (complete example)
• Exponential logistic curve (complete example)
• Double power curve (complete example)

Complex survey data examples:

• A measurement model   (complete example)
• A structural equation model   (complete example)
• A generalized linear model   (complete example)
• A generalized linear model (complete example)
• A generalized linear model  (complete example)
• GLIMS for continuous responses   (complete example)
• Confirmatory factor analysis model   (complete example)
• Confirmatory factor analysis model with latent variable relationship and latent variable means   (complete example)
• GLIMS for count data using substance abuse data   (complete example)
• GLIMS for binary responses   (complete example)
• GLIMS for ordinal responses using substance abuse data   (complete example)
• GLIMS for nominal responses using NHIS data   (complete example)
• A structural equation model for the 2001 monitoring the future data   (complete example)
• Implementation of sampling weights in a linear growth curve model   (complete example)
• Simulation study based on a linear growth curve model   (complete example)
• Latent curve analysis with main and interaction effects  (complete example)
• Replicate weights   (complete example)
• Analyzing count data and correcting for over-dispersion (complete example)

Multilevel Generalized Linear Modeling examples:

• Binary case: a 2-level model    (complete example)
• Binary model with logit link function   (complete example)
• Binary models with probit link function   (complete example)
• Bernoulli models for NESARC data (complete example)
• Bernoulli distribution with complementary log-log link function   (complete example)
• Multilevel models for categorical and count data    (complete example)
• Models for count outcomes from the NESARC data   (complete example)
• Models for count outcomes using ASPART data   (complete example)
• Negative binomial model for the NESARC data   (complete example)
• The data for an ordinal approach   (complete example)
• Models for ordinal outcomes using NIMH data   (complete example)
• An ordinal regression model with random intercept   (complete example)
• Poisson log model with an offset variable   (complete example)
• Poisson model for the Thailand data (complete example)
• Poisson model and scale parameter estimation for NIH data (complete example)
• Three-level Poisson models for simulated data (complete example)
• Negative binomial model for the NIH data (complete example)
• Models for nominal outcomes using NHIS data   (complete example)
• Models for proportional and non-proportional odds   (complete example)
• Two-level survival analysis models  (complete example)
• Weighted 2-level models   (complete example)

Analysis of ordinal data

The examples below correspond to a note by Karl Jöreskog on how to analyze ordinal data in LISREL. The original note can be found here. The examples given here have been edited to reflect these analyses using LISREL 11.

• Cross-sectional data (complete example)
• Longitudinal data (complete example)
• Multiple groups (complete example)
• Covariates (complete example)

Examples from Multivariate Analysis with LISREL

A selection of examples in this section are based on the text Multivariate Analysis with LISREL, by  Jöreskog, K.G., Olsson, U. H. & Wallentin, F.Y., (2016), Springer. For the complete examples, please see the text. To download all examples associated with this text, click here.

Examples from Chapter 2:

• Linear regression: fitness data (complete example)
• Linear regression: income data (complete example)
• Linear regression and instrumental variables (complete example)
• Univariate regression: hypotheses testing (complete example)
• Conditional regression: math on reading data (complete example)
• Conditional regression: birthweight data (complete example)
• Multivariate regression: test scores (complete example)
• Multivariate regression: hypotheses testing (complete example)
• Non-recursive model: income data (complete example)
• Non-recursive LISREL model: income data (complete example)
• Recursive model: textile workers union data (complete example)
• Logistic and probit regression: credit risk data (complete example)
• Logistic regression: death penalty data (complete example)
• Multivariate censored regression (complete example)

Examples from Chapter 3:

• Binomial logit and probit models: death penalty data (complete example)
• Log-linear model: melanoma data (complete example)
• Nominal logistic regression: program choices (complete example)
• Ordinal logistic model: car data (complete example)
• Ordinal logistic model: mental health data (complete example)
• Poisson model: heart disease data (complete example)
• Poisson model with categorical covariate (complete example)

Examples from Chapter 4:

• Multilevel and conditional regression comparison (complete example)
• Multilevel analysis of repeated measures (complete example)
• Multilevel analysis with cross-level interaction (complete example)
• Multivariate analysis of the Netherlands data (complete example)
• Multilevel Generalized Linear Model for social mobility (complete example)

Examples from Chapter 5:

• Principal component analysis of stock market data (complete example)
• Principal component analysis of nine psychological variables (complete example)
• Principal component analysis of meteorological data (complete data)

Examples from Chapter 6:

• Exploratory factor analysis of ordinal LSAT data (complete data)
• Exploratory factor analysis of polytomous data (complete data)
• Exploratory factor analysis: hypothetical population (complete data)

Examples from Chapter 7:

• Confirmatory factor analysis of ordinal data with missing values (complete example)
• Confirmatory factor analysis of ordinal data without missing values (complete example)
• Confirmatory factor analysis of ordinal data without missing values (complete example)
• Confirmatory factor analysis of reader reliability (complete example)

Examples from Chapter 8:

• SEM for the role behavior of farm managers (complete example)
• Second-order factor analysis of 9 psychological variables (complete example)

Examples from Chapter 9:

• Latent growth curve for dyadic data (complete example)
• Learning curves of air traffic controllers (complete example)
• Panel model for political efficacy data (complete example)

Examples from Chapter 10:

• Confirmatory factor analysis for multiple groups using school data (complete example)
• Confirmatory factor analysis for ordinal data from 8 countries (complete example)
• Twin data models: heredity of BMI (complete example)