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A Unifying Account of Spurious Multidimensionality in Psychological Questionnaires

REČKA, Karel and David ELEK

Basic information

Original name

A Unifying Account of Spurious Multidimensionality in Psychological Questionnaires

Authors

REČKA, Karel and David ELEK

Edition

Psychoco 2024, 2024

Other information

Language

English

Type of outcome

Presentations at conferences

Country of publisher

Netherlands

Confidentiality degree

is not subject to a state or trade secret

References:

Organization

Fakulta sociálních studií – Repository – Repository

Keywords in English

spurious multidimensionality; Likert scales; factor analysis.

Links

GA23-06924S, research and development project.
Changed: 29/3/2025 00:50, RNDr. Daniel Jakubík

Abstract

V originále

Psychological questionnaires, often designed to measure latent constructs, frequently exhibit spurious multidimensionality, particularly when incorporating a mix of regular and reversed items. Existing explanations attribute this multidimensionality to construct-irrelevant factors (such as) or consider it a spurious outcome resulting from imperfections of the measurement model. This presentation focuses on the phenomenon of spurious multidimensionality, a unifying account of why it can arise. We posit that a primary cause of spurious dimensionality lies in an incorrectly specified item response function, where the empirical and model-implied relationships between a latent variable and its indicators differ. Then, when multiple items share a similar pattern of these discrepancies (residuals), a unidimensional model will not fit the data, necessitating the introduction of additional factors to account for the residual relationships between items. An empirical study supported our predictions. Items exhibiting a shared pattern of residuals tended to form an additional factor. Importantly, this factor still contained construct-relevant variance. Consequently, our findings underscore the importance of scrutinizing whether the relationship between a latent variable and its indicators is modeled correctly to avoid spurious multidimensionality. Otherwise, there is always a risk that spurious factors will be interpreted substantively.

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