Construct validity, Polychoric correlations, Pearson correlation, Factor analysis,

The aim of this study was to validate a Spanish version of the Cognitive Emotion Regulation Questionnaire (CERQ-S), originally developed by Garnefski, Kraaij, and Spinhoven. To date, it is the only available instrument that permits a conceptually pure quantification of cognitive strategies of emotional regulation. A sample of 615 students (25% men; 75% women) completed the CERQ-S. Confirmatory factor analyses showed that, as in the original version, a nine-factor model also explained the data collected with the Spanish version. However, an alternative model that integrates the nine dimensions in two second-order factors shows appropriate global fit indices and has interesting implications. Likewise, the results of the present study are comparable with those obtained in previous work with measures of depression, anxiety, and anger, and increase support for the validity of this instrument for assessing normalized affective states.

No abstract

The widespread use of Pearson correlations and, by extension, the Maximum Likelihood estimation method, does not take into account the measurement properties of Likert scales observed variables when carrying out a construct validity process through Confirmatory Factor Analysis (CFA). This simulation study compares four estimation methods (Maximum Likelihood -ML-, Robust Maximum Likelihood -RML-, Robust Unweighted Least Squares -, RULS) according to two of the assumptions CFA is supposed to fulfil: multivariate normality and, especially, the continuous measurement nature of both latent and observed variables. Goodness of fit is diagnosed by χ 2 Likelihood Ratio Test and RMSEA indices. Results suggest ULS and RULS are preferable as polychoric correlations help to overcome grouping and transformation errors produced when using Pearson correlations for ordinal observed variables. Data measurement scale consideration enhances the ability of hypothesized models to reproduce accurately construct variables relationships.