Table 2.

Correlations Between Criterion Variables (Appearance Satisfaction and Disordered Eating) and SATAQ-4R Internalization: Thin/Low Body Fat Subscale and Ideal Body Stereotype Scale-Revised (IBSS-R) Using a Bifactor Model (n = 1094)

	Bifactor Model
Criterion Variable	General ωHierarchical = .62	SATAQ-4R ωHierarchical Subscale = .37	IBSS-R ωHierarchical Subscale = .39
Appearance Satisfactiona ω = .91	−.36*** (.04)	−.30*** (.04)	−.06 ns (.04)
Restraintb ω = .85	.35*** (.04)	.36*** (.04)	.15*** (.04)
Eating Concernc ω = .84	.40*** (.04)	.34*** (.04)	.09* (.04)
Shape Concernd ω = .92	.43*** (.04)	.43*** (.04)	.24*** (.04)
Weight Concerne ω = .88	.40*** (.04)	.40*** (.04)	.23*** (.04)

Note. Composite reliability or omega (ω) was computed for the criterion variables from the one-factor confirmatory factor analysis model for each scale.

$$\mathrm{\omega }=\frac{{({\sum }_{i=1}^p{\lambda }_{\mathit{\text{ij}}})}^2}{{({\sum }_{i=1}^p{\lambda }_{\mathit{\text{ij}}})}^2+{\sum }_{i=1}^p{\theta }_{\mathit{\text{ii}}}}$$

where λ_ij is the standardized factor loading of item i on factor j and θ is the standardized unique variance of the item.¹³

$$\mathrm{\omega }\text{ Hierarchical}=\frac{{(\sum \lambda \text{ General})}^{\mathbf{2}}}{{(\sum \lambda \text{ General})}^{\mathbf{2}}+{(\sum \lambda \text{ SATAQ})}^{\mathbf{2}}+{(\sum \lambda \text{ IBSS})}^{\mathbf{2}}+\sum (1-{\mathrm{h}}^2)}$$

$$\mathrm{\omega }\text{ Hierarchical Subscale for SATAQ}=\frac{{(\sum \lambda \text{ SATAQ})}^{\mathbf{2}}}{{(\sum \lambda \text{ General})}^{\mathbf{2}}+{(\sum \lambda \text{ SATAQ})}^{\mathbf{2}}+\sum (1-{\mathrm{h}}^2)}$$

The standardized parameter estimates for the four SATAQ items (general and specific factor loadings and unique variance) are used in the computations.

$$\mathrm{\omega }\text{ Hierarchical Subscale for IBSS}=\frac{{(\sum \lambda \text{ IBSS})}^{\mathbf{2}}}{{(\sum \lambda \text{ General})}^{\mathbf{2}}+{(\sum \lambda \text{ IBSS})}^{\mathbf{2}}+\sum (1-{\mathrm{h}}^2)}$$

The standardized parameter estimates for the six IBSS items (general and specific factor loadings and unique variance) are used in the computations.²²

^aA parameter estimating the correlation between the errors for MBSRQ-AE 1 and MBSRQ-AE 3 was added to the model.

^bA parameter estimating the correlation between the errors for EDEQ 2 and EDEQ 5 was added to the model.

^cA parameter estimating the correlation between the errors for EDEQ 19 and EDEQ 21 was added to the model.

^dA parameter estimating the correlation between the errors for EDEQ 27 and EDEQ 28 was added to the model.

^eA parameter estimating the correlation between the errors for EDEQ 8 and EDEQ 25 was added to the model.

^*p < .05.

^***p < .001.

ns = not statistically signifi