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Psychology 202b Advanced Psychological Statistics, II April 5, 2011
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The Plan for Today Homework and exam remediation Recap of path analysis by hand Assumptions Path analysis using SEM Introducing Mplus Estimating disturbances Assessing model fit
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Homework Update on where we are. The disk system on faculty.ucmerced.edu thinks it is full. I cannot post sadistic Homework 5. Substitute: one more chance to submit a late homework; your choice which one, but only one.
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Exam remediation A one-week take-home exam will be available Tuesday. Students who elect to take it to improve their scores will be on their honor to work alone.
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Path Analysis So far, we have learned that manual path analysis is hard unless the model is saturated. To avoid the pain of the past, I did not make us suffer through unsaturated models by hand. Now that you have learned something about path analysis, what should you ask next?
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Assumptions Linear relationships. Independence. Normal errors. No reverse causation. Exogenous variables are without error. State of equilibrium. Correct model specification.
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Path analysis with SEM What if we had a way to select the best solution from the many possible solutions for an over-identified model? Maximum likelihood using the idea that the covariance matrix follows a Wishart distribution. That’s what SEM software does.
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Software for SEM Lisrel Amos EQS Mplus (free demo version available) R’s sem package
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Introducing Mplus A free demonstration version can be downloaded here.here Demo version is limited to 2 exogenous and 6 endogenous variables. Otherwise, fully functional.
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Using Mplus Simple example: multiple regression. A saturated path analysis. An unsaturated path analysis. That is much easier than manual path analysis.
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Estimating disturbances So far, we haven’t bothered adding disturbances to our path models. Using SEM output, it’s easy. Disturbances are just the square root of the residual variances.
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Assessing model fit Indices of model fit: –The chi-square (compares the model to the saturated model). –The RMSEA –CFI and TLI Useful reference here.here Comparing models: –The likelihood-ratio test
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Next time Exploratory factor analysis.
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