LISREL - Complex Examples

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)

• 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)