Assessing the measurement model (MM) of self-report scales is crucial to obtain valid measurement of individuals' latent psychological constructs. This entails evaluating the number of measured constructs and determining which construct is measured by which item. Exploratory factor analysis (EFA) is the most-used method to evaluate these psychometric properties, where the number of measured constructs (i.e., factors) is assessed, and, afterwards, rotational freedom is resolved to interpret these factors. This study assessed the effects of an acquiescence response style (ARS) on EFA for unidimensional and multidimensional (un)balanced scales. Specifically, we evaluated (i) whether ARS is captured as an additional factor, (ii) the effect of different rotation approaches on the recovery of the content and ARS factors, and (iii) the effect of extracting the additional ARS factor on the recovery of factor loadings. ARS was often captured as an additional factor in balanced scales when it was strong. For these scales, ignoring (i.e., not extracting) this additional ARS factor, or rotating to simple structure when extracting it, harmed the recovery of the original MM by introducing bias in loadings and cross-loadings. These issues were avoided by using informed rotation approaches (i.e., target rotation), where (part of) the MM is specified a priori. Not extracting the additional ARS factor did not affect the loading recovery in unbalanced scales. Researchers should consider the potential presence of an additional ARS factor when assessing the psychometric properties of balanced scales, and use informed rotation approaches when suspecting that an additional factor is an ARS factor.
- Response styles
- Exploratory factor analysis (EFA)
- categorical data
- response bias