LISREL for Windows - A brief overview
During the last thirty eight years, the LISREL model, methods and software have become synonymous with structural equation modeling (SEM). SEM allows researchers in the social sciences, management sciences, behavioral sciences, biological sciences, educational sciences and other fields to empirically assess their theories. These theories are usually formulated as theoretical models for observed and latent (unobservable) variables. If data are collected for the observed variables of the theoretical model, the LISREL program can be used to fit the model to the data.
Today, however, LISREL for Windows is no longer limited to SEM. The latest LISREL for Windows includes the following statistical applications.
LISREL for structural equation modeling.
PRELIS for data manipulations and basic statistical analyses.
MULTILEV for hierarchical linear and non-linear modeling.
SURVEYGLIM for generalized linear modeling.
MAPGLIM for generalized linear modeling for multilevel data.
L LISREL
The 32-bit application LISREL is intended for:
Standard structural equation modeling
Multilevel structural equation modeling
These methods are available for the following data types:
Complete and incomplete complex survey data on categorical and continuous variables
Complete and incomplete simple random sample data on categorical and continuous variables
PRELIS
PRELIS is a 32-bit application which can be used for:
Data manipulation
Data transformation
Data generatiion
Computing moment matrices
Computing asymptotic covariance matrices of sample moments
Imputation by matching
Multiple imputation
Multiple linear regression
Logistic regression
Univariate and multivariate censored regression
ML and MINRES exploratory factor analysis
M MULTILEV
MULTILEV fits multilevel linear and nonlinear models to multilevel data from simple random and complex survey designs. It allows for models with continuous and categorical response variables.
S SURVEYGLIM
SURVEYGLIM fits Generalized LInear Models (GLIMs) to data from simple random and complex survey designs.
Models for the following sampling distributions are available.
Multinomial
Bernoulli
Binomial
Negative Binomial
Poisson
Normal
Gamma
Inverse Gaussian
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