dimensionality decision with bootEGA
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I am employing bootEGA to determine dimensionality, and I've observed a discrepancy in the decision when utilizing raw data compared to the polychoric matrix. The items under consideration are ordinal, featuring 4 or 5 categories each. The raw data bootEGA unequivocally indicates the presence of 4 dimensions, whereas the polychoric matrix bootEGA suggests 3 dimensions.
This inconsistency arises exclusively when employing the "glasso" method, as both decisions align when using the "tmfg" approach. Upon scrutinizing my data, I noted a lack of multivariate normality, which leads me to speculate whether this non-normality is a key factor influencing the discrepancy. Consequently, should I prioritize the "tmfg" method for its robustness in handling non-normally distributed data?
Thank you very much for dedicating your time to assist me in this matter. Your guidance is highly appreciated.