During the last thirty 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.

LISREL for structural equation modeling.

 

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 continuous variables
Complete and incomplete simple random sample data on ordinal and continuous variables

PRELIS for data manipulations and basic statistical analyses.

 

PRELIS is a 32-bit application which can be used for:

Data manipulation
Data transformation
Data generation
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

MULTILEV for hierarchical linear and non-linear modeling.

 

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.
CONFIRM for formative inference-based recursive modeling for continuous response variables.

 

CONFIRM implements formal inference-based recursive modeling for continuous outcome variables.

CONFIRM for formative inference-based recursive modeling for continuous response variables.

 

CONFIRM implements formal inference-based recursive modeling for continuous outcome variab

MAPGLIM for generalized linear modeling for multilevel data.

 

MAPGLIM implements the Maximum A Priori (MAP) method to fit generalized linear models to multilevel data.

SURVEYGLIM for generalized linear modeling.

 

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


© Copyright 2005-2017, Scientific Software International, Inc.

Software originalmente sviluppato per la stima di modelli di equazioni strutturali (SEM). Oggi comprende molte altre applicazioni statistiche.