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Omega hierarchical (reliability)
My snobby psychometrics colleagues don't like alpha (even though it's used 98% of the time), because one can get a high alpha even if one has no general factor. Omega (hierarchical; not general) is the solution. I am writing to plea for consideration for future JMP (or if anyone is sufficiently challenged, an add-in). Thanks.
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Re: Omega hierarchical (reliability)
Make sure you submit the request to the JMP Wish List?
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Re: Omega hierarchical (reliability)
Thank you @profjmb! It's a great suggestion. I just added it to our to-do list. We'll eventually get to it!
Best,
~Laura
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Re: Omega hierarchical (reliability)
Hello @profjmb,
I just wanted to let you know that JMP 16.0 will have an option to obtain coefficient omega from a CFA. Whether users obtain omega hierarchical or general will depend of the type of CFA that was fit. For example, a standard CFA with 3 factors would result in omega_general for subscales. However, if such CFA is extended to a bifactor model (by adding a general factor that loads on all manifest variables), the result will be omega_hierarchical for the general factor and omega_hierarchical for subscales for the group factors. This follows the review of omega coefficients in Rodriguez, Reise, & Haviland (2015). These options are available in the Early Adopter program so we'll keep improving them as we receive feedback.
Thank you again for your suggestion!
~Laura
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Re: Omega hierarchical (reliability)
Hi Laura,
Thanks for the info.
I'm trying to obtain the coefficient omega using the early adopter but I cannot find it.
Please could you provide indications about where to find it in the program?
Thanks
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Re: Omega hierarchical (reliability)
Dear @Fernando,
We included coefficient omega as part of a "mini dashboard" of related statistics that quantify the adequacy of the measurement model at hand, thus, you'll find it in under the red triangle menu for a fitted model as, "Assess Measurement Model."
Best,
~Laura