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GRA 6020 Multivariate Statistics Confirmatory Factor Analysis. Ulf H. Olsson Professor of Statistics. 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
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GRA 6020Multivariate StatisticsConfirmatory Factor Analysis Ulf H. Olsson Professor of Statistics
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
THE IDEA OF THE RMSEA True Process Empirical Domain Theoretical Domain 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
Other Fit Indices • CN • RMR • GFI • AGFI • Evaluation of Reliability • MI: Modification Indices Ulf H. Olsson
Nine Psychological Tests/Matrix Notation Ulf H. Olsson
Variance Equation and Composite Reliability Ulf H. Olsson