Hi guys, my name is Bas and welcome to the 24th episode of my SPSS tutorials. Please like and subscribe, and if you have any remaining questions please leave them in the comment section down below.
Bedankt voor alle filmpjes! Stel de factorlading is 0.613 op de bedoelde factor en 0.349 bij een andere (onbedoelde)? Moet de variabele dan worden verwijderd? Het voldoet wel wel aan de >.60 eis bij de eigen maar niet aan 0.3 meer op eigen dan op andere eis?
Hi, thank you a lot for this good presentation but I did not understand a point I would like to test the homogeneity to use ANOVA I have a normal distribution Do I base of the KOM or Signification de Bartelett value, please help me
Thanks for the presentation, can we do KMO test and Bartlett Test for Sphericity for a questionnaire only having categorical data (nominal and ordinal) ? Also is it suitable to do it when using Principal component analysis (PCA)
I've got a set of data from a pilot test. The questionnaire includes 72 items for measuring stress. When we run factor analysis, the KMO is really low, 0.18. I was wondering how we deal with the data in such a circumstance Thanks in advance
So you ran a factor analysis? (Kmo is part of the factor analysis). Is your dataset complete? Did you select the right options to show? Did you select all variables? If you met all requirements above then I sadly don't know the answer. Do other analyses work? You could google "no spss factory output" and maybe find the answer that way
Maybe one of your selected variables has no variance, that's an scenario where spss doesn't run the factor analysis.In that case scenario i would evaluate the teorethical construction of your scale to decide if the variable is adecuate and necessary or no for your model. If not u can try deleting the variable with no variance and use the new analysis to reformulate the theoretical construction and then run again (if possible) the data collection with the new teorethical model.