By Timothy A. Brown PsyD
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Additional info for Confirmatory Factor Analysis for Applied Research
2, the degrees of freedom associated with the χ2 fit statistic is 2, corresponding to the difference a – b, 10 – 8 = 2; see Chapter 3). However, two factors cannot be extracted, because the number of parameters to be estimated in this model exceeds the number of elements of the input matrix by one, that is, a = (4 ∗ 2) + [(2 ∗ 3) / 2)] + 4 – 4 = 8 + 3 + 4 – 4 = 11. Each aspect of the equation used to solve for a corresponds to specific parameters and mathematical restrictions in the EFA model (cf.
Thus, because the applied CFA researcher must have a working knowledge of EFA, the methods of conducting an EFA are reviewed in this chapter. This overview is also provided to allow more detailed comparisons of EFA and CFA in later chapters. , psychology, education, sociology, management, public health). The fundamental intent of factor analysis is to determine the number and nature of 12 The Common Factor Model and EFA 13 latent variables or factors that account for the variation and covariation among a set of observed measures, commonly referred to as indicators.
The higher up the axis, the higher the factor loading; if an indicator is in close proximity to one factor axis, it does not load highly on another factor. 4B, orthogonal rotation moved the Factor 2 axis closer to the Y5–Y8 indicators. 4A). 244 for the unrotated and rotated solutions, respectively. 4B), the restriction of maintaining a 90° orientation of the factor axes may not be tenable. Oblique rotations such as promax begin with an orthogonal rotation, but then “break” the 90° angle to allow the factor axes to pass through the clusters of indicators better.