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GRA 6020 Multivariate Statistics Confirmatory Factor Analysis

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 6020 Multivariate Statistics Confirmatory Factor Analysis

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  1. GRA 6020Multivariate StatisticsConfirmatory Factor Analysis Ulf H. Olsson Professor of Statistics

  2. 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

  3. THE IDEA OF THE RMSEA True Process Empirical Domain Theoretical Domain Ulf H. Olsson

  4. Alternative test- Testing Close fit Ulf H. Olsson

  5. 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

  6. Other Fit Indices • CN • RMR • GFI • AGFI • Evaluation of Reliability • MI: Modification Indices Ulf H. Olsson

  7. Nine Psychological Tests/Matrix Notation Ulf H. Olsson

  8. Variance Equation and Composite Reliability Ulf H. Olsson

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