Lecture16_SEMBasics

Lecture16_SEMBasics - Structural Equation Modeling (SEM)...

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2/1/11 Structural Equation Modeling (SEM) – Some Basic Concepts Kathryn Sharpe & Wei Zhu
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2/1/11 2 SEM Basics Ø SEM is a statistical technique for testing and estimating causal relationships first proposed in 1921 by the American Geneticist Dr. Sewall Green
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2/1/11 33 SEM Basics Ø SEM without latent variables is called Path Analysis . Ø SEM is a confirmatory analysis procedure although sometimes it can also be used as an exploratory analysis tool. Ø SEM is a set of usually inter-related linear regression equations.
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2/1/11 44 A simple example: Path Diagrams & Equations for Every variable with an incoming arrow leads to a regression equation. Our regression equation system is as follows: Obj102 Obj103 Obj104 Obj105 Directional Arrows indicate cause and effect
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2/1/11 55 SEM Programs For this example, we will use PROC CALIS. It takes our linear equations (previous slide) and estimates the parameters for the model. Then it evaluates the goodness of fit of the model. PROC CALIS (and PROC TCALIS) in SAS LISREL ( Karl Gustav Jöreskog & Dag Sörbom) EQS ( Peter Bentler, UCLA ) AMOS The most popular software packages for SEM are:
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2/1/11 6 Dr. Karl Gustav Jöreskog (Sweden) Widely viewed as leaders in SEM development in our times
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2/1/11 77 SAS Code Give the linear equations describing the system Suppress Pearson correlations Proc calis: use cov rather than corr SAS correlation procedure Give variances of exogenous variables Error variances Specifies output Dataset with type Covariance matrix proc corr cov nocorr data=eddata outp=edcova(type=cov); run ; proc calis cov mod data=edcova; Lineqs bi = b1 am + b2 sw + E1, sw = b3 am + b4 bi + E2, dt = b5 bi + b6 sw + E3, rd = b7 dt + E4 ; Std E1-E4 = The1-The4 ; Cov E1 E2 = Ps1; Run ; We must set the error equal to a parameter value; otherwise it is assumed to be 0 BI and SW are correlated so we must estimate the correlation of their error terms’ variances
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2/1/11 88 Results of SAS Analysis:
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Lecture16_SEMBasics - Structural Equation Modeling (SEM)...

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