In the last forty-five years, the LISREL model, methods and software have become synonymous with structural equation modeling (SEM). SEM allows researchers from the social sciences, management sciences, behavioral sciences, biological sciences, educational sciences, and other fields to empirically evaluate their theories.
In the last forty-five years, the LISREL model, methods and software have become synonymous with structural equation modeling (SEM). SEM allows researchers from the social sciences, management sciences, behavioral sciences, biological sciences, educational sciences, and other fields to empirically evaluate their theories. These theories are generally formulated as theoretical models for observed and latent (non-observable) variables. If data is collected for the observed variables of the target model, the LISREL program can be used to fit the model to the data.
Today, however, LISREL is no longer limited to SEM. LISREL includes statistical 64-bit applications LISREL, PRELIS, MULTILEV, SURVEYGLIM and MAPGLIM.
PRELIS
PRELIS is a 64-bit application for data manipulation, data transformation, data generation, computational moment matrices, calculating estimated asyinthtic covariance matrices of sample moments, correspondence imputation, multiple imputation, multiple linear regression, logistic regression, univariate and multivariate censored regression, and exploratory factor analysis of ML and MINRES.
MULTILEV
MULTILEV is a 64-bit application that adapts linear and nonlinear multilevel models to multilevel data from simple random and complex search projects. Allows models with continuous and categorical response variables.
SURVEYGLIM
SURVEYGLIM is a 64-bit application that adapts to Generalized Linear Models (GLIMs) to the data of simple and random complex search projects. Models are available for multinomial, Bernoulli, Binomial, Binomial Negative, Poisson, Normal, Gamma and Gaussiana Inverse sampling distributions.
MAPGLIM
is a 64-bit application that implements the Maximum A Priori (MAP) method to fit generalized linear models to multilevel data.
System requirements
Operating system: Windows 7, 8, 10
Min. CPU: Processor 486 or higher
Min. RAM: 16 MB the RAM
Disk space: 10 MB
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