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I have used EFA with geomin rotation on a sample of 319 respondents. I am in a similar situation to many of the people who have posted on this thread. A reviewer has asked me for the percent of variance explained. I have reviewed every post, and I understand that % variance explained is a measure for PCA, not EFA, and that the goal of EFA is to reproduce the correlation matrix. In doing some reading about summarizing and reporting EFA, I found a citation that suggests that the percentage of explained variance can serve as a means of assessing how much the correlation matrix is reproduced. The citation can be found here: LorenzoSeva, U. (2013). How to report the percentage of explained common variance in exploratory factor analysis. Technical Report. Department of Psychology, Universitat Rovira i Virgili, Tarragona. Document available at: http://psico.fcep.urv.cat/utilitats/factor/ I have two questions: 1. Is reporting the percentage of explained common variance a reasonable way to summarize a oblique rotation? (In the working paper, LorenzoSeva uses Varimax) 2. Is there a way to calculate the percentage of explained common variance in MPlus? Thanks for your help with this! Meredith 


With an orthogonal rotation, you can sum the squared factors loadings and divide by the number of factor indicators. There is no option for this in Mplus. 

Shirley posted on Friday, June 02, 2017  3:11 am



Dear Dr. Muthen, I have a survey of 12 items on 3 scales. As a few of the items are positively worded, I fit a CFA with 3 trait factors and 1 method factor (as shown below). The 3trait1method model fit significantly better than the original 3traitfactor model and had better fit statistics (e.g., RMSEA). As the original 3traitfactor model provides acceptable fit and is the hypothesis, I am interested to examine the impact of this method factor (similar to the idea of ECV in the previous post). In the CFA context, may I check if the following equation is appropriate? (% of variance in the data the method factor accounts for)=(sum of the squared STDYX loadings on the 3 trait factors from all 12 items)/((sum of the squared STDYX loadings on the 3 trait factors from all 12 items)+(sum of the squared STDYX loadings on the method factor from the 4 crossloading items))? Thanks! ********************************* VARIABLE: [omitted] CATEGORICAL=q1q12; CLUSTER=teacher; ANALYSIS: TYPE=COMPLEX; MODEL: f1 by q1* q2q4; f2 by q5* q6q8; f3 by q9* q10q12; Method by q1* q2 q5 q11; f1Method@1; Method WITH f1f3@0; 


I think your numerator should instead be (sum of the squared STDYX loadings on the method factor from the 4 crossloading items) Otherwise ok. 

Shirley posted on Sunday, June 04, 2017  8:04 pm



Thanks for spotting the oversight in the equation! 

fred posted on Saturday, May 11, 2019  8:23 am



Hi, Am I correct to assume that sum of sq loadings divided by n of indicators is not appropriate in Geomin roatated EFA.? Is there then a similar way for the geomin (or other oblique rotations) to get the explained variance? I am familiar with discussion on the issue not being the goal of EFA, still the journal reviewers tend to require the % explained v, I guess because of PCA being the prototype and tradition. 


I don't think it is appropriate with correlated factors. 

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