Statistical Power in Structural Equation Modeling
By T. Oertzen, C. Hertzog, Paolo Ghisletta, Ulman E. R. Lindenberger. 2007
86 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/f5e11c9d0487254e8ab72aa02921cd8e69744b05
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Carol Stoak Saunders
- Qing Chang
- Stephen A. Sivo
- James J. Jiang
- Timothy A. Brown
- Olaf Gjerløw Aasland
- E. Falkum
- Ellen Melbye Langballe
Citations in the corpus
- The Factorial Validity of the Maslach Burnout Inventory–General Survey in Representative Samples of Eight Different Occupational Groups (2006, result): “The fact that the analyses in this research are conducted on large representative data sets with samples of relatively similar sizes provides the tests with solid statistical power (Kaplan, 1995) and warrants generalization of the findings to the specific occupational groups in Norway.”
- How Low Should You Go? Low Response Rates and the Validity of Inference in IS Questionnaire Research (2006, methodology): “Power analysis should be an essential facet of CFA or SEM research (Fan and Sivo, 2005; Gefen et al., 2000; Kaplan, 1990; Lei and Dunbar, 2004; Muthen and Muthen, 2002; Saris and Satorra, 1993; Sivo, Fan, Witta, and Willse, 2006).”
- Confirmatory Factor Analysis for Applied Research (2006, methodology): “Step 4. Premultiply the random data matrix (X) with the pattern matrix (F) to create the correlated data matrix (Z). The fundamental equation of the Kaiser and Dickman (1962) matrix decomposition procedure is”