This paper introduces a novel analytical framework for calculating standard errors in exploratory factor analysis. The method provides a unified approach for various extraction rules, offering a practical alternative to computationally intensive resampling techniques. The derived standard errors are accurate, straightforward to compute, and remain valid even under non-Gaussian conditions, with simulations confirming their effectiveness and an application demonstrating their impact on inference. AI
RANK_REASON The cluster contains an academic paper detailing a new statistical methodology. [lever_c_demoted from research: ic=1 ai=0.4]
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