Random intercept EFA of personality scales

Abstract

HighlightsRandom Intercept EFA (RI-EFA) adjusts for acquiescence bias in self-reports.RI-EFA was examined with regard to the NEO-FFI and BFI personality scales.RI-EFA provides better model-to-data fit than standard CFA or EFA.The clarity of Big Five factor structures improves when applying RI-EFA.RI-EFA can be extended to further analytical applications.

Acquiescence in personality questionnaires: Relevance, domain specificity, and stability

“…To evaluate the relevance of acquiescence in personality questionnaires we analyzed data of a short instrument assessing the Big Five in two large scale studies representative of the adult population of the two countries. The results suggest that acquiescence accounts for about 4% of the variance of personality items, which is similar to what previous research has found (e.g., Aichholzer, 2014;Billiet & McClendon, 2000;Rorer & Goldberg, 1965). At first glance, this number suggests only a minor influence of acquiescence on personality items.…”

“…This can substantially bias correlations between items (Bentler et al, 1971), factor structures of personality inventories (Aichholzer, 2014;Rammstedt & Farmer, 2013), comparability of personality assessments across countries (Rammstedt, Kemper, & Borg, 2013) and (as shown in the present research) the suitability of underlying measurement models, and bias the correlation between personality items and criterion variables. Therefore, acquiescence should not be ignored (cf.…”

“…After controlling for acquiescence, however, these coefficients markedly increased in strength, thus indicating that the adjective ratings are severely affected by acquiescence. In the same vein, Rammstedt and colleagues (Rammstedt & Farmer, 2013;Rammstedt, Goldberg, & Borg, 2010;Rammstedt & Kemper, 2011) and Aichholzer (2014) showed that acquiescence can even affect the factor structure of established personality questionnaires. Based on large scale data, the authors demonstrated that the initial factor loadings were inconsistent with the expected Big Five factor structure.…”

“…1 As suggested by Aichholzer (2014), we also ran the analysis using unrestricted factor loadings (EFA) for the BFI items with Exploratory Structural Equation Modeling (ESEM; Asparouhov & Muthén, 2009). Generally, the model fit of ESEM is better than the model fit of standard structural equation models because ESEM allows cross-loadings between manifest items and latent factors.…”

“…Thus, the acquiescence specificity of the sum score is (3 P 10 i¼1 x i /r sum = (3 ⁄ 10 ⁄ 0.04)/16.80 = 0.07. and measurement error. In particular, the structural equation modeling approach by Billiet and McClendon (2000) provides a promising way that has already been applied in other studies (e.g., Aichholzer, 2014;Billiet & Davidov, 2008). An alternative approach to control for acquiescence on item level can be ipsative transformation of the items' raw scores.…”