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Psychology 202b Advanced Psychological Statistics, II. April 5, 2011. The Plan for Today. Homework and exam remediation Recap of path analysis by hand Assumptions Path analysis using SEM Introducing M plus Estimating disturbances Assessing model fit. Homework. - PowerPoint PPT Presentation
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Psychology 202bAdvanced Psychological
Statistics, II
April 5, 2011
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
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.
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.
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?
Assumptions
• Linear relationships.• Independence.• Normal errors.• No reverse causation.• Exogenous variables are without error.• State of equilibrium.• Correct model specification.
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.
Software for SEM
• Lisrel• Amos• EQS• Mplus (free demo version available)• R’s sem package
Introducing Mplus
• A free demonstration version can be downloaded here.
• Demo version is limited to 2 exogenous and 6 endogenous variables.
• Otherwise, fully functional.
Using Mplus
• Simple example: multiple regression.• A saturated path analysis.• An unsaturated path analysis.• That is much easier than manual path
analysis.
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.
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.• Comparing models:
– The likelihood-ratio test
Next time
• Exploratory factor analysis.
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