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:
Lorenzo-Seva, 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, Lorenzo-Seva uses Varimax)
2. Is there a way to calculate the percentage of explained common variance in MPlus?
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 3-trait-1-method model fit significantly better than the original 3-trait-factor model and had better fit statistics (e.g., RMSEA). As the original 3-trait-factor 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 cross-loading items))?
Thanks! ********************************* VARIABLE: [omitted] CATEGORICAL=q1-q12; CLUSTER=teacher; ANALYSIS: TYPE=COMPLEX; MODEL: f1 by q1* q2-q4; f2 by q5* q6-q8; f3 by q9* q10-q12; Method by q1* q2 q5 q11; f1-Method@1; Method WITH f1-f3@0;
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.