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# Get Higher Performance with Structural Equation Modeling by pptfiles

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```									Get Higher Performance with Structural Equation Modeling
Tim Daciuk David Matheson Arik Pelkey
August 2008

Agenda
      

What is SEM? What is AMOS Who uses AMOS? How does AMOS fit in?

What are the benefits?
Demonstration How do I get started?

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

Q&A
Summary

Structural Equation Modeling: A Primer and Simple Example

Attend.=Bx*   0  +i B0 yi   i i i Temp.  

Latent

What is Structural Equation Modeling (SEM)


A general, powerful multivariate analysis technique


Includes specialized versions of a number of other analysis methods as special cases



Factor analysis, path analysis and regression all represent special cases of SEM. SEM largely confirmatory, rather than exploratory Usually focuses on latent constructs A relatively young field

  

What is SEM?
   

Suitable for complex systems
Models can include latent variables Diagnostics

Basic Terminology


Standard Structural Equation

ev   sc  cv  d 


Path Analytic Equation

ev    pc  cv    p  d 
     

ev = effect variable pc = path coefficient sc = structural coefficient cv = causal variable p = path d = disturbance

Basic Terminology - II
  

Standardized Variable


Variable whose mean is zero and variance is one.
A variable in the model that is not measured. A variable that is not caused by another variable in the model. A variable that is caused by one or more variable in the model.

Latent Variable
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Exogenous Variable


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Endogenous Variable
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Basic Terminology - III
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Structural Coefficient


A measure of the amount of change in the effect variable expected given a one unit change in the causal variable and no change in any other variable.

  

Disturbance
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The set of unspecified causes of the effect variable.
A set of structural equations. A diagram that pictorially represents a structural model.

Structural Model
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Path Diagram


    

Model Specification

Identification
Estimation Testing Fit Model Modification or Respecification

What is AMOS
  

Our Structural Equation Modeling application
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Latest is 17.0

Model complex systems Model effects that can’t be directly measured

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

Graphic user interface is easy to use
Stand alone or used in conjunction with SPSS

And What’s New in AMOS 17.0
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Copy and paste a path diagram from one Amos Graphics window to another
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Also part of a path diagram

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Convert path diagram to equivalent VB Enhanced growth curve
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Automatically constrains parameters
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Appropriate for many growth curve models

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Program changes
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Default value for ‘all groups’ checkbox New PathDiagrammer method, EditPaste New PathDiagrammer method, ToolsWriteAProgram ImputeNo now called Imputation_

Who uses AMOS?
     

Social scientists

Market researchers
Political analysts Psychologists Educators Physicians

Major Applications of SEM


Causal modeling, or path analysis


Hypothesizes causal relationships among variables and tests the causal models with a linear equation system. Extension of factor analysis in which specific hypotheses about the structure of the factor loadings and intercorrelations are tested;
Variation of factor analysis in which the correlation matrix of the common factors is itself factor analyzed to provide second order factors;

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Confirmatory factor analysis
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Second order factor analysis
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Major Applications of SEM
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Regression models
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Extension of linear regression analysis in which regression weights may be constrained to be equal to each other, or to specified numerical values;



Covariance structure models
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Hypothesize that a covariance matrix has a particular form. For example, you can test the hypothesis that a set of variables all have equal variances
Hypothesize that a correlation matrix has a particular form. A classic example is the hypothesis that the correlation matrix has the structure of a circumplex



Correlation structure models
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Structured Equation Modeling and the Path Diagram


Y = aX + E
  

All independent variables have arrows pointing to the dependent variable. The weighting coefficient is placed above the arrow. Variables are represented in ovals or rectangles.




Manifest variables are placed in boxes in the path diagram. Latent variables are placed in an oval or circle.

e
E

2

x

2

X

a

Y

Structured Equation Modeling and the Path Diagram


Y = aX + E


For example, the variable E in the diagram can be thought of as a linear regression residual when Y is predicted from X. Such a residual is not observed directly, but calculated from Y and X, so we treat it as a latent variable and place it in an oval.

e
E

2

x

2

X

a

Y

Demonstration of AMOS

What can I do with AMOS?
  

Multiple equation models

Include factors that can’t be directly measured
More options for dealing with missing data

How Does AMOS Fit?


Structural equation modeling is now a well accepted technique Required in many fields Natural progression from regression and factor analysis Diagnostics similar to traditional methods

 



Questions

?

What are the Benefits?
    

Realism

Accuracy
Graphic representation Create models easily Options for power users

How do I Get Started?
     

Demo on same disk as SPSS 17 and modules

Easy to use graphic interface

Introduction to AMOS 17.0
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Technical: http://www.spss.com/amos/
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Product literature and white papers Recorded seminars Citations

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www.amosdevelopment.com
 

Amos development Corp. Examples, videos, bibliography, links, etc.

 

Pricing: your rep or sales@spss.com Tim Daciuk,
  

Director, Worldwide Demo Resources tdaciuk@spss.com (416) 410-7921

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