Kaiser-Meyer-Olkin (KMO) Test - How to Interpret Properly
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- Опубликовано: 8 фев 2025
- Many sources suggest that a KMO value of larger than .50 suggests the data are appropriate for factor analysis. In this video, I demonstrated that this suggesting is misleading. Instead, on the basis of Kaiser and Rice (1974), I suggest a value of .65 or larger to support the application of a factor analysis.
Kaiser, H. F., & Rice, J. (1974). Little jiffy, mark IV. Educational and psychological measurement, 34(1), 111-117.
Thank you so much for taking the time to make these videos. They are always a huge help!
Thank you so much sir.... u proved an information is wealth 😊 keep on helping like this ❤
Many thanks for this video - it has saved my thesis bacon. xx
Amazing insights! 💯
Thanks! This video is really nice!
Nice! This has been such a big headache for me... every different article I find claims a different number between 0.6 to 0.8
In this video you talk about 0.65 as the minimum KMO value for factor analysis, can you please provide a citation for the same?
Many thanks! Informative
Thank you Sir, actually I am using River water samples data. I would like to perform PCA and some other statistical methods but I found KMO coefiicient less than even 0.4. please any help?
why I run the test but table for KMO and Bartlett test is not appear.. I do click that.. why?
Great Job! like.
hi,
useful video,I am getting chi square value 1.00E4 , can someone help me to figure out the error/problem
Thank you very much for the video Dr. TL Todd. I did not however get the point of 'mixture of positive and negative correlation matrix' right. Again you mentioned for symmetrical data SPSS give a KMO value of 0.5 hence your rejection of value as suggestive of appropriate factor in dataset. My question is is this true for other softwares? Thank you
Ha! I'm not Dr. Todd. This is how2stats (Dr. Gignac). I don't think I said symmetrical data. It would be more accurate to say an identity matrix (all .00, except for the variances) yields a KMO value of .50; however, a correlation matrix with a mixture of positive and negative correlations can also yield an average correlation of .00. I don't know about KMO in other programs, but I would be surprised if they calculated it differently.
Hey, my p-value for Bartlet's test is 6e-125 which shows it is fit for dimensionality reduction but overall MSA(KMO) = 0.04 which shows is not good for factor analysis. What does this mean?
What if it's 0.515, Is it possible to manipulate data and improve to to 0.65 at least? Just asking.
I doubt it. Look at the inter-item correlations, you'll see that they are probably all very low (say, < .09)
what is the df. value pls ?
There are no degrees of freedom to consider, in this context; it's more of an effect size approach.
what author are you based on to say that it should have a value of .65
It's my own recommendation, based on Kaiser's table. You can find some books that recommend .60 or greater, if you Google it.
@@how2statsthanks
May I have the reference link of this paper?
Kaiser, H. F., & Rice, J. (1974). Little jiffy, mark IV. Educational and psychological measurement, 34(1), 111-117.
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