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Based on these findings it can be concluded that a single factor model best fits the data in the study.
A two-factor model offered an acceptable account of the data; however, when a single correlated error involving two highly similar items was included, a single factor model fit the data very well.
The hypothesized measurement model fit the data better than a single factor model: χ 2 (158, N = 572) = 594.29, p = 0.00; RMSEA = 0.088 900 % CI 0.079 to 0.096); CFI = 0.881; and AIC = 738.29) both in terms of the fit statistics and when directly contrasted with a change in AIC.
Model 1 (see Figure 1) tested the cross-group fit of a single factor model.
We fitted a single factor model to each group to ensure that the measurement model fit appropriately.
These findings provide further support for a single factor model underlying the multiple aspects of autistic traits and symptoms.
A model with a single factor (model A) was tested in order to obtain a basis for comparison with dual models.
A single factor model in which all items load onto a single factor was also fit for reference to the other CFA models.
In a study of patients with AIDS, Rosenfeld et al [ 20] found that a 3-factor model fitted the data better than a single factor model did.
Factor analysis was used to test that the five items fit a single factor model of a comprehensive measurement of well-baby visits.
The suitability of a single factor model underlying 10-item CD-RISC was analyzed by confirmatory factor analysis (CFA) with IBM SPSS Amos 19 software.
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