During the last thirty years, the LISREL model,methods and software have become synonymous with structuralequation modeling (SEM). SEM allows researchers in the socialsciences, management sciences, behavioral sciences, biologicalsciences, educational sciences and other fields to empiricallyassess their theories. These theories are usually formulated astheoretical models for observed and latent (unobservable)variables. If data are collected for the observed variables of thetheoretical model, the LISREL program can be used to fit the modelto the data.

LISREL is developed by Scientific Software International, Inc. And is used by 4 users of Software Informer. The most popular version of this product among our users is 8.8. The names of program executable files are LisWin32.EXE, Icon7D809841.exe, LISWIN.EXE, liswin32.exe.1a1.exe and RunDll32.ex. LISREL is the progenitor of structural equation modeling, since 1976. Item Response Theory BILOG-MG and PARSCALE have enabled IRT applications in educational measurement. LISREL can help the user to identify the interaction effects that need to be included in the model and the ones that do not need to be included in the model. The indicative information can be used in diagnosing the model specification. To purchase LISREL or for a free trial version, click here. Related Analyses: SEM. LISREL, Free Download by Scientific Software International, Inc. Suite of tools which ensure your privacy and keep sensitive information secure.

Here are some key features of”LISREL”:
– Structured latent curve models
The LISREL CO command has been extended to include the exponential(EXP) and natural logarithm (LOG) operators as well as parentheses.This allows LISREL users to fit, for example, the structured latentcurve models outlined in Browne (1993).

– Factor analysis of ordinal variables
Classical exploratory factor analysis assumes that the observedvariables are continuous. The PRELIS OFA command implementsexploratory factor analysis of ordinal variables as described inJöreskog & Moustaki (2006).

– Generalized linear models (GLIMs) for multileveldata
The new statistical application MAPGLIM fits generalized linearmodels to multilevel data. Users can select from the multinomial,Bernoulli, Poisson, binomial, negative binomial, Normal, Gamma andinverse Gaussian sampling distributions. The corresponding linkfunctions include the log, cumulative logit, cumulative probit,complementary log-log and logit link functions.

– Observational residuals
Bollen and Arminger (1991) introduced observational residuals forstructural equation models. LISREL 8.8 for Windows allows users tocompute observational residuals along with latent variable scoresfor the latent variables of the model. This implementation isdescribed and illustrated in Jöreskog, Sörbom & Wallentin(2006)

– Writing parameter estimates, standard error estimates andmeasures of fit to a PSF
The PV, SV and GF keywords on the LISREL OU command or the SIMPLISLISREL output command have been extended to allow users to save theparameter estimates, standard error estimates and measures of fitto a PSF. This is especially useful for Monte Carlo studies.

– Changes to the graphical user interface(GUI)
The main window of LISREL 8.8 for Windows is now entitled LISRELfor Windows. The revised Export Data option on the File menu of themain window allows users to export data to various data formatssuch as SPSS, SAS, SYSTAT, Statistica, etc.

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