Statistics: Posted by mcfanda@gmail.com — Mon Dec 10, 2018 11:18 am

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Statistics: Posted by mcfanda@gmail.com — Fri Nov 30, 2018 5:38 pm

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This is our overall design. Could you please advise? We are happy to clarify additional details regarding the study if needed. Thank you!

Statistics: Posted by nwong12 — Thu Nov 29, 2018 11:19 pm

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As regards the correspondence of a mixed model results with the eZANOVA or similar packages results, it depends on the design and the way the mixed model is defined. If you post your design, we can see what is the model that better suits your needs.

As regards the df, also the df depends on how you specify the model. More specifically, the df depend on what are the random effects in the model and their variance. Thus, to understand the df, you need to clarify how the random effects are defined.

Statistics: Posted by mcfanda@gmail.com — Wed Nov 28, 2018 12:18 am

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We used GAMLj and our results showed the df from the intercept, rather than each variable.

Thanks in advance!

Statistics: Posted by nwong12 — Tue Nov 27, 2018 9:45 pm

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we would really love to tell students - use jamovi instead of spss - but when we can not reproduce (or understand) the results

if you can relax the assumption that spss is correct, or "most correct", or "the gold standard", you'll probably have an easier time of this. but i appreciate that can be challenging (especially with colleagues).

have you heard the story about the lavaan sem package? people were always complaining that it didn't provide *exactly* the same results as the commercial packages, so yves rosseel ended up reverse engineering the other packages, figuring out *exactly* what they did (which wasn't quite correct), and then adding options to mimic the (not quite correct) output from other packages.

cheers

jonathon

Statistics: Posted by jonathon — Tue Nov 13, 2018 10:28 pm

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Statistics: Posted by Ravi — Tue Nov 13, 2018 1:38 pm

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maybe SPSS uses the principal components analysis eigenvalues to conduct the parallel analysis? I double checked it in R using the psych package and it's also giving me negative eigenvalues there. Also, here's an example of STATA producing negative eigenvalues: https://stats.idre.ucla.edu/stata/faq/h ... -in-stata/. So I assume there's not an issue with negative eigenvalues, but I am curious to know about the discrepancies between SPSS and jamovi/R/STATA.

Ravi

Statistics: Posted by Ravi — Tue Nov 13, 2018 1:31 pm

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Ravi wrote:

Ok, I now added 'maximum likelihood' and 'principal axis factoring' as possible extraction methods (next to the 'minimum residual' method). Should be available in the next version. Is there another extraction method that you think should be added?

Ok, I now added 'maximum likelihood' and 'principal axis factoring' as possible extraction methods (next to the 'minimum residual' method). Should be available in the next version. Is there another extraction method that you think should be added?

Thats really, really cool !! I tried the new version 0.9.5.8. and was really thrilled to see principal axis factoring - as option to choose. So i tried it - but still get Initial Eigenvalues below Zero - in Spss the values of the Eigenvalues add up to the number of factors (items) you analyse - so either (and thats quite possible) there is something I dont understand (and theres lots of that) or maybe there is a bug in the analysis provided. Maybe you could check this.

Reason I write is - we would really love to tell students - use jamovi instead of spss - but when we can not reproduce (or understand) the results, which are different from what we teach students, we will have to wait - when it comes to prinicipal axis factoring - and it would be so cool - if this works out, cause spss does not do parallel analyses (except if you bring in a few sheets of syntax code) - and jamovi would be a really good alternativ for students.

Statistics: Posted by Paul L — Tue Nov 13, 2018 12:23 pm

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Statistics: Posted by Ravi — Thu Oct 25, 2018 1:08 pm

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Statistics: Posted by ftr — Wed Oct 24, 2018 9:06 pm

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A list can be found here: https://www.ibm.com/support/knowledgece ... t_ext.html

Although with Maximum Likelihood, minimum residuals, and PAF included with Jmaovi, I think it would satisfy the majority's factor extraction needs.

Thanks again!

Statistics: Posted by statsnewbie — Tue Oct 23, 2018 5:43 am

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Cheers,

Ravi

Statistics: Posted by Ravi — Sun Oct 21, 2018 7:19 pm

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