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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. 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.
- CATFIRM for formative inference-based recursive modeling for categorical response variables.
- CONFIRM for formative inference-based recursive modeling for continuous response variables
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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 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
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.
SURVEYGLIM.EXE 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
CATFIRM implements formal inference-based recursive modeling for categorical outcome variables.
CONFIRM implements formal inference-based recursive modeling for continuous outcome variables.
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