ArticleFrontiers in psychology2021
Reliability Estimation in Multidimensional Scales: Comparing the Bias of Six Estimators in Measures With a Bifactor Structure.
Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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26 citing papers in PubMed.
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- Observational
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- Psychometric Evaluation of the School Climate and School Identification Measure-Student on Chilean Students: A Bifactor Model Approach.Children (Basel, Switzerland) · 2024Article
- Comparison of different reliability estimation methods for single-item assessment: a simulation study.Frontiers in psychology · 2024Article
- Validation of the Arabic Version of the Patient Activation Measure (PAM-13) for Application within the Primary Healthcare Context in Saudi Arabia.Healthcare (Basel, Switzerland) · 2023Article
- Measuring provider well-being: initial validation of a brief engagement survey.BMC health services research · 2023Article
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5 authors.
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Abstract
In the context of multidimensional structures, with the presence of a common factor and multiple specific or group factors, estimates of reliability require specific estimators. The use of classical procedures such as the alpha coefficient or omega total that ignore structural complexity are not appropriate, since they can lead to strongly biased estimates. Through a simulation study, the bias of six estimators of reliability in multidimensional measures was evaluated and compared. The study is complemented by an empirical illustration that exemplifies the procedure. Results showed that the estimators with the lowest bias in the estimation of the total reliability parameter are omega total, the two versions of greatest lower bound (GLB) and the alpha coefficient, which in turn are also those that produce the highest overestimation of the reliability of the general factor. Nevertheless, the most appropriate estimators, in that they produce less biased estimates of the reliability parameter of the general factor, are omega limit and omega hierarchical.
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