2012
DOI: 10.4324/9780203851319
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A Beginner's Guide to Structural Equation Modeling

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Cited by 969 publications
(1,200 citation statements)
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“…A lower Chi Square value indicates a better fit, however, the X 2 value in this study was 198 with 73 degrees of freedom and was significant .001. For models with more than 200 cases (in our case 550), the chi square is almost always statistically significant (Schumacker & Lomax, 1996). For these reasons A Measure of Metacognitive Beliefs in Health Anxiety 9 9 alternative fit indices were used to assess model fit.…”
Section: Resultsmentioning
confidence: 96%
“…A lower Chi Square value indicates a better fit, however, the X 2 value in this study was 198 with 73 degrees of freedom and was significant .001. For models with more than 200 cases (in our case 550), the chi square is almost always statistically significant (Schumacker & Lomax, 1996). For these reasons A Measure of Metacognitive Beliefs in Health Anxiety 9 9 alternative fit indices were used to assess model fit.…”
Section: Resultsmentioning
confidence: 96%
“…In all the analyses, standard errors of parameters were estimated according to the method of maximum likelihood. To evaluate the global adjustment quality of the model we considered the CFI (Comparative Fit-Index) and GFI (Goodness-of-Fit Index) above.90, the w 2 /degrees of freedom ratio around 2, and the RMSEA (Root Mean Square Error of Approximation) below .05 as indicating a good fit of the model to the data (e.g., Schumacker and Lomax, 1996).…”
Section: Discussionmentioning
confidence: 99%
“…Possible non-linearity suggested by Figures 1 and 2 was explored by comparing the fit of linear and quadratic structural models. Both models added age as a predictor of both factors in the model, while the quadratic model also included the squared age variable (Schumacker & Lomax, 2010). In the absence of any established guidelines for assessing meaningful change in a structural model, the chi-square difference test was used along with R 2 change to indicate the size of any quadratic effect.…”
Section: Structural Regression Modelsmentioning
confidence: 99%
“…To examine whether the association of age with happiness was moderated by GDP, the fit of two models was compared: (a) where regression paths of age were free to vary across GDP groups, and (b) where regression paths were constrained to equality across GDP groups for each factor (Schumacker & Lomax, 2010).…”
Section: Structural Regression Modelsmentioning
confidence: 99%