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Lecture1 PDF .pdf

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Structural Equation Modeling (SEM) using AMOS
Structural Equation Modeling (SEM) is an extension of the general linear model. It is
used to test a set of regression equations simultaneously. The advantages of SEM Analysis
are as follows:
 SEM provides overall tests of model fit and individual parameter estimate tests
 Regression coefficients, means and variances may be compared simultaneously.
 It is the graphical interface software.
What is SEM?
SEM represents the relationship between dependent (unobserved) variable and
independent (observed) variables using path diagrams.
 In this analysis, ovals or circles represent dependent variable.
 Rectangles or squares represent independent variable.
 Residuals (error term) variables also represent by ovals or circles, because they are
always unobserved.
What are the values extracted from the Test?
If the hypothesized model has a good fit, the statistical test values should be in the
following manner.
 Chi-square value should be less than 5
 P value should be greater than 0.05
 GFI, AGFI and CFI values should be greater than 0.90
 RMR & RMSEA values should be less than 0.08

Upcoming Weeks…..
Lecture -2
Structural Equation Modeling (SEM) using AMOS
1. Latent Variables
2. Observed or manifest variables

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