Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Test Statistics for Confirmatory Factor Analysis Under Non-Normality and Large p/n Ratios: A Comment on Muda and Yangxuan (2026). |
| Συγγραφείς: |
Foldnes, Njål1 (AUTHOR) njal.foldnes@uis.no, Grønneberg, Steffen2 (AUTHOR) |
| Πηγή: |
Structural Equation Modeling. Sep/Oct2026, Vol. 33 Issue 5, p678-682. 5p. |
| Θεματικοί όροι: |
*Confirmatory factor analysis, *High-dimensional model representation |
| Περίληψη: |
Muda and Yangxuan recommended a ridge-calibrated test statistic for controlling Type I error inflation in confirmatory factor analysis under non-normality. Although improving finite-sample inference is an important goal, their empirical evaluation is undermined by incorrectly implemented benchmark statistics, misattributed comparison methods, and a simulation design restricted to asymptotically robust conditions. Using corrected code, we reanalyze the original conditions and replace the misattributed benchmarks with the penalized eigenvalue procedures pEBA 4 RLS and pOLS 2 RLS . Under the original conditions, the best-performing procedures are the ridge-calibrated TCsFCr statistic and the penalized eigenvalue methods. However, under additional non-asymptotically robust conditions, including high-dimensional models, pEBA 4 RLS provides the most reliable Type I error control and outperforms the ridge-calibrated competitors. [ABSTRACT FROM AUTHOR] |
| Βάση Δεδομένων: |
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