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Hello, I did an exploratory factor analysis in SPSS which suggested 4 clear factors. One factor in particular has four items with factor loadings all greater than .79. However, when I plug these items in to CFA in MPlus, only two items have high factor loadings (>0.83) and the two others are low (<0.36). Can you explain this? Thanks. |
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The 4-factor SPSS analysis determined the loadings for the 4 items by not only the correlations among the 4 items but also by their correlations with other items. If you redo the SPSS analysis with only those 4 items you probably get more similar results to the CFA. Assuming that you are using estimators that are the same or similar. |
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Thank you for your reply. I redid the SPSS with only those 4 items, and 3 loaded at > 0.98 and one loaded at about 0.80. I'm not strong in statistics, and I don't really know what you mean by estimators, but I told SPSS to use maximum likelihood with PROMAX rotation. I guess what I really need to know is whether I should bank on Mplus's CFA analysis -- and therefore assume that those four items are not loading on the same factor. Thanks again! |
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If you treat the items as continuous (the Mplus default) and use the ML estimator in both programs, the loadings are going to be exactly the same since CFA with 1 factor is the same as EFA with 1 factor. So something else is going on that I can't see. Note also that when you do the CFA and want the results in the same metric as the EFA, fix the factor variance at 1 and free the first factor loading. A 1-factor CFA with some large and some small loadings does not invalidate the hypothesis of a single factor. That should instead be determined by the chi-square test of model fit. |
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I have categorical items and I'm using WLSMV in Mplus. Do you think that could be accounting for the difference? Should I change the estimator in either SPSS or Mplus? Thank you so much for your help. |
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I don't know if SPSS can handle categorical items. You can't compare results from one program treating the items as continuous and therefore using a linear factor model with results from another program treating the items as categorical and therefore using a non-linear (probit/logit) factor model. You will be fine using WLSMV in Mplus treating the items as categorical. |
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Thank you. Would you confirm that I should think of what I call "ordinal" level items as "categorical" in Mplus? |
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That's right. |
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Thanks for your assistance! |
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Hi, I've got a dataset with 23 items (rated 1-7 scale). I've run an EFA in SPSS (prinicipal axis factoring, varimax rotation, 2 factors extracted) and found that 2 factors accounted for well over half the variance in the dataset and the loadings of the items make perfect theoretical sense. When I got to test the model in CFA (2 factor model), the fit indices (CMIN, RMSEA, CFI, NFI, etc.) are all really bad. I am wondering if you might be able to help me understand what might be happening (or point me to an article that could)? Thanks! Steve |
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Your SPSS EFA does not give you standard errors of the rotated factor loadings and therefore does not give you information about significant cross-loadings which when fixed at zero in CFA causes misfit. Mplus EFA will give you this information. You also don't have to impose the strong structure of the CFA - for more on that I suggest that you read about the new idea of "ESEM": Marsh, H.W., Muthén, B., Asparouhov, A., Lüdtke, O., Robitzsch, A., Morin, A.J.S., & Trautwein, U. (2009). Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students’ Evaluations of University Teaching. Forthcoming in Structural Equation Modeling. and also the Asparouhov-Muthen article both on the Mplus web site at http://www.statmodel.com/esem.shtml |
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Hello, I have a strange output for my EFA with categorical items using a complex data set. My models run, but the chi square result is *******. Could you please explain this result? Thank you. Heidi |
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The value is too large to fit in the space provided. For further information, send your output and license number to support@statmodel.com. |
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Daniel Lee posted on Tuesday, March 24, 2015 - 12:21 pm
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Hi Dr. Muthen, I have a very short 4-item scale and would like to run an EFA and CFA for 1 and 2 factor solution. I know that a 2 factor solution is a saturated model (that's the limit). I tried running the CFA of the 2-factor solution and it worked just fine. However, when running a two-factor solution with EFA, mplus indicated that too many factors were requested. Can you briefly tell me why a CFA can be conducted, but not an EFA for the 2-factor solution of a 4-item scale? |
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The are many more parameters in an EFA than a CFA. See the Topic 1 course handout and video on the website where this is discussed. Slide 104 gives the formula for the number of factors that can be extracted for a given number of variables. |
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Daniel Lee posted on Wednesday, March 25, 2015 - 7:36 am
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Thank you Dr. Muthen! |
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