使用期限*
许可形式单机
原产地美国
介质下载
适用平台windows
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LISREL (Jöreskog & Sörbom 2006) may be used to fit multiple group structural equation models to multiple
group data. Traditional statistical methods such as Maximum Likelihood (), Robust Maximum Likelihood
(RML), Weighted Least Squares (WLS), Diagonally Weighted Least Squares (DWLS), Generalized Least
Squares (GLS) and Un-weighted Least Squares (ULS) are available for complete multiple group data while
the Full Information Maximum Likelihood (FIML) method is available for incomplete multiple group data.
The , RML, WLS, DWLS, GLS and ULS methods for multiple group structural equation modeling are
described in Jöreskog & Sörbom (1999) while the FIML method is described in Du Toit & Du Toit (2001).
![lisrel正版软件怎么买](//l.b2b168.com/2018/11/24/13/201811241328274599504.jpg)
The results
The results are written to the output file, SEM.OUT, which consists of several sections. In this section, we
will review some selections of this output file. The sample covariance matrix is shown in the following
text editor window
![lisrel正版软件怎么买](//l.b2b168.com/2020/06/18/16/202006181652223170044.jpg)
The small P-value suggests that there is sufficient evidence that weak invariance does not hold for the
measurement model in Figure 1 across gender.
Strong invariance
The measurement model in Figure 1 is said to have strong invariance if the model is the same with identical
factor loadings and means across boys and girls. This is assessed as follows.
• Select the Close all option on the Windows menu.
• Use the Open option on the File menu to load the Open dialog box.
• Browse for the location C:\LISREL Student Examples\TUTORIAL.
• Select the file SINV.SPL by clicking on it.
• Click on the Open button to open the following text editor window.
![lisrel正版软件怎么买](//l.b2b168.com/2020/06/18/15/202006181534397471204.jpg)
LISREL provides tools for structural equation modeling, data manipulations and basic statistical analyses, hierarchical and non-linear modeling, generalized linear modeling, and generalized linear modeling for multilevel data.
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