I really like the explanation but you misspoke: oblimin is an OBLIQUE rotation does the factors end up CORRELATED and Varimax was supposed to be described as ORTHOGONAL so the result is UNCORRELATED. Otherwise thank you very clear explanation
Each line reprsents a factor. The idea of the factors is to represent a multidimensional space (variables) with a smaller number of dimensions (the factors). In this example the general factor tells which direction the observatiosn are from the origin and the second which direction they are related to the first factor. Does this help?
@@mronkkoso If I understand it correctly: - The red line shows which observations / items are above the line and which are below (seperating them into 2 factors) - The black line is to point to the 2 seperate clumps of items that each represent a factor - and the Orange line is to make that pointing more specific Is that correct? Are those the steps you need to follow or something?
@@jannomeeuwessen4886 The red coordinate system is the unrotated factor solution. The black coordinate system is a rotated factor analysis with orthogonal rotation. The orange coordinate system is a rotated factor analysis with oblique rotation. You would generally first estimate the unrotated solution. Whether it is printed out or not depends on statistical software. Then you would do either orthogonal or oblique rotation. The oblique rotation is typically a better choice (at least for the kinds of problems I use factor analysis for.)
I've been trying to understand this concept after reading about it and watching lectures, you explained it in 7 minutes perfectly. Subscribed.
I really like the explanation but you misspoke: oblimin is an OBLIQUE rotation does the factors end up CORRELATED and Varimax was supposed to be described as ORTHOGONAL so the result is UNCORRELATED. Otherwise thank you very clear explanation
@@mronkko when you first defined oblique and orthogonal around 3:50 you said it backwards (you said oblique maintains uncorrelated factors).
Thanks! the rule of thumb is really helpful
You are welcome!
Thanks for doing this video! it was helpful for me.
very well-explained, thank you!
How can i do factor rotation in matlab?
Thanks!
You are welcome!
I thought I understood it until he drew the Orange and Black axis lol
Why are there multiple axis? The first one he drew (red) should be enough right
Each line reprsents a factor. The idea of the factors is to represent a multidimensional space (variables) with a smaller number of dimensions (the factors). In this example the general factor tells which direction the observatiosn are from the origin and the second which direction they are related to the first factor. Does this help?
@@mronkkoso If I understand it correctly:
- The red line shows which observations / items are above the line and which are below (seperating them into 2 factors)
- The black line is to point to the 2 seperate clumps of items that each represent a factor
- and the Orange line is to make that pointing more specific
Is that correct? Are those the steps you need to follow or something?
@@jannomeeuwessen4886 The red coordinate system is the unrotated factor solution. The black coordinate system is a rotated factor analysis with orthogonal rotation. The orange coordinate system is a rotated factor analysis with oblique rotation.
You would generally first estimate the unrotated solution. Whether it is printed out or not depends on statistical software. Then you would do either orthogonal or oblique rotation. The oblique rotation is typically a better choice (at least for the kinds of problems I use factor analysis for.)
great vid but it doesn't show me How To ...
The "How to" part is software specific and typically you just pick a rotation method from a dropdown menu.
baadiya tha
You are welcome, I suppose.
Sound too soft
Yes. I am aware of the problem. I asked our video editor to fix the audio levels, but that has not happened yet.