Measurement Models Ulf H. Olsson Professor of Statistics.

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Presentation transcript:

Measurement Models Ulf H. Olsson Professor of Statistics

Ulf H. Olsson Kaplan ch.3 3.1and 3.2 is important 3.3 Rotation: Have to know what it is, not mathematically 3.4 EFA, will be demonstrated 3.5 Testing the CFA: Very important

Ulf H. Olsson CFA and ML k is the number of manifest variables. If the observed variables comes from a multivariate normal distribution, and the model holds in the population, then

Ulf H. Olsson Problems with the chi-square test The chi-square tends to be large in large samples if the model does not hold It is based on the assumption that the model holds in the population It is assumed that the observed variables comes from a multivariate normal distribution => The chi-square test might be to strict, since it is based on unreasonable assumptions?!

Ulf H. Olsson Alternative test- Testing Close fit

Ulf H. Olsson How to Use RMSEA Use the 90% Confidence interval for EA Use The P-value for EA RMSEA as a descriptive Measure RMSEA< 0.05 Good Fit 0.05 < RMSEA < 0.08 Acceptable Fit RMSEA > 0.10 Not Acceptable Fit

Ulf H. Olsson The CFA model Estimating the model Testing the model (Does the model fit the data?) Chi-square RMSEA Other fit indices Re-specify the model (MI) Does the model make sense?

Ulf H. Olsson Examples Nine Psychological tests Ability and Aspiration Ambivalence From EFA to CFA The files are available on Blackboard

Ulf H. Olsson Nine Psychological Tests

Ulf H. Olsson CFA= Measurement Model Reflective measures Reliability Composite Reliability

Ulf H. Olsson Assignments from week 35-36

Ulf H. Olsson Assignments next week ABILITY AND ASPIRATIONS NINE PSYCH. TESTS AMBIVALENCE AND SATIFACTION SEE WORD FILE FOR DETAILS