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Embrace the Heterogeneity in Exploratory Factor Analysis But Be Transparent About What You Do-A Commentary on Manapat et al. (2023)
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DOI：10.1037/met0000759.png)
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Abstract
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Manapat et al. (2023) investigated different sources of heterogeneity in exploratory factor analysis in their paper Evaluating Avoidable Heterogeneity in Exploratory Factor Analysis Results. Their study is an important step toward understanding the volatility of factor analysis results that potentially impair replication attempts in psychology. In this short commentary, we want to address the question which heterogeneity is actually avoidable and which heterogeneity can also be desirable in an exploratory analysis. Furthermore, we emphasize the need of greater research transparency when performing and reporting exploratory factor analyses and discuss the potential of preregistrations to avoid unwanted or avoidable heterogeneity. When being transparent about methodological decisions and conceptual assumptions that lead to specific configurations, we believe that it is possible to embrace the heterogeneity in exploratory factor analysis and still develop more robust measurement models.
Keywords:
exploratory factor analysis
replication
measurement model
transparency
open science
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