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I wonder whether the ideal number of factor to retain with a bifactor efa is N or N+1, given N is the number of factor suggested by parallel analysis. Because a perfect 5 factor oblique structure would be best recovered by 6 (and not 5) factors with a bi-factor efa (1 general & 5 specific). What would you recommend ? Best regards Philippe |
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Bi-factor EFA with 1 general and m-1 specific factors has the same model fit (same ML loglikelihood and number of parameters) as an m-factor regular EFA. So bi-factor EFA with a total number of m factors is just a different rotation than the m-factor EFA. In your case, if you have perfect fit for 5 EFA factors, you would also have that same perfect fit for a bi-factor model with 1 general and 4 specific factors. So, if parallel analysis suggests 5 factors, you can go with bi-factor using 1 general and 4 specifics; i.e. asking for 5 factors when doing bi-factor EFA. |
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Thank you very much. That makes a lot of sense. |
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Mplus User posted on Thursday, February 22, 2018 - 10:54 am
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I know this is available somewhere and I can't seem to find it. What is the syntax for specifying a bifactor EFA? VARIABLE: NAMES ARE x1-x16; USEVARIABLES x1-x16; ANALYSIS: TYPE = EFA 1 6; |
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UG Chapter 4 covers EFA. UGex 4.7 shows bi-factor EFA. |
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Mplus User posted on Monday, February 26, 2018 - 7:45 am
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Thank you! For a bifactor EFA, do you recommend the BI-GEOMIN rotation or the BI-CF-QUARTIMAX rotation? I have a model with 2 specific correlated factors and 1 general factor, and I have interval data. |
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No recommendation - they shouldn't be too different. Interpretability should be the primary guide. |
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