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EFA/ CFA (Measurement Models)

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Title: EFA/ CFA (Measurement Models)


1
EFA/ CFA (Measurement Models)
  • Ulf H. Olsson
  • Professor of Statistics

2
Factor Analysis
  • Exploratory Factor Analysis (EFA)
  • One wants to explore the empirical data to
    discover and detect characteristic features and
    interesting relationships without imposing any
    definite model on the data
  • Confirmatory Factor Analysis (CFA)
  • One builds a model assumed to describe, explain,
    or account for the empirical data in terms of
    relatively few parameters. The model is based on
    a priori information about the data structure in
    form of a specified theory or hypothesis

3
The EFA model
4
EFA
  • Eigenvalue of factor j
  • The total contribution of factor j to the total
    variance of the entire set of variables
  • Comunality of variable i
  • The common variance of a variable. The portion of
    a variables total variance that is accounted for
    by the common factors

5
The CFA model
  • In a confirmatory factor analysis, the
    investigator has such a knowledge about the
    factorial nature of the variables that he/she is
    able to specify that each xi depends only on a
    few of the factors. If xi does not depend on
    faktor j, the factor loading lambdaij is zero

6
Nine Psychological Tests(EFA)
7
Nine Psychological Tests(CFA)
8
Measurement Models
  • Consequences of Measurement Error
  • Biased estimates
  • Does the Model fit the Data
  • The Chi-square test
  • The RMSEA approach
  • Detailed evaluation of the model
  • Reliability
  • Validity

9
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
10
Testing Exact Fit
11
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
  • gt The chi-square test might be to strict, since
    it is based on unreasonable assumptions?!

12
Alternative test- Testing Close fit
13
How to Use RMSEA
  • Use the 90 Confidence interval for EA
  • Use The P-value for EA
  • RMSEA as a descriptive Measure
  • RMSEAlt 0.05 Good Fit
  • 0.05 lt RMSEA lt 0.08 Acceptable Fit
  • RMSEA gt 0.10 Not Acceptable Fit

14
Other Fit Indices
  • CN
  • RMR
  • GFI
  • AGFI
  • Evaluation of Reliability
  • MI Modification Indices
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