Thank you for this video. so helpful. Question. I have a data set with 1003 participants. I used 16 questions exploring overall attitudes of grandparents. When i do the factor analysis on these questions extracts 4 components. However, when I split the file by gender, the males extract 5 components and the females 4. SPSS created 5 new variables. Should I not split the file?
Thanks, but after we have the factors as in your case five ones, how we can have single measure for all these factors. Since our objective by using factor analysis is to reduce the number of variables to only one variable
Hi Ankita. It's very hard to know what's going on without seeing data, but I'd probably start by asking why you chose a Promax rotation? That allows for correlations between your factors, which, in must contexts isn't ideal if you're trying to actually learn from the factors (it can be useful in ML contexts for purely data reduction purposes). That's why I recommend the varimax rotation as it maximizes the interpretability of the factors.
@@DataDemystified thanks for quick response , its antecedents and we expect correlation, and my guide asked me to use oblimin but promaz gives clearer pattern . Also, do you know whats is kappa in promax please?
@@ankitatibrewal6842 Both rotations should yield very similar results. Again, without seeing the data, it's hard to say. Also, why are you running a factor analysis in the first place? Can you describe the situation more? It's hard to help with such limited information.
Hi there. If you're referring to the anit-image correlation matrix, we use that to look at the diagonals. We are looking for measures of sampling adequacy at the individual item level (>.5 is considered adequate).
Best video I've seen on the topic.
Excellent video and wonderful explanation. This has been absolutely helpful for me
Thanks. This is very helpful and explained very clearly.
This tutorial is amazing
literally helpful and amazing
what a useful video! excellent.
Excellent video!
Glad you liked it!
Thank you for this video. so helpful. Question. I have a data set with 1003 participants. I used 16 questions exploring overall attitudes of grandparents. When i do the factor analysis on these questions extracts 4 components. However, when I split the file by gender, the males extract 5 components and the females 4. SPSS created 5 new variables. Should I not split the file?
well done.
Thanks
Please, how does the Factor Analysis relate to Cronbach Alpha analysis. What is the difference and similarities.
Can we conduct the factor analysis of the each factor separately? Will that be possible?
please explain on the interpretation of the factor loading
Thanks, but after we have the factors as in your case five ones, how we can have single measure for all these factors. Since our objective by using factor analysis is to reduce the number of variables to only one variable
The objective of FA is to reduce the data into fewer variables, not necessarily one.
My results are acceptable in Promax but not oblimin rotation, can you guide why?
Hi Ankita. It's very hard to know what's going on without seeing data, but I'd probably start by asking why you chose a Promax rotation? That allows for correlations between your factors, which, in must contexts isn't ideal if you're trying to actually learn from the factors (it can be useful in ML contexts for purely data reduction purposes). That's why I recommend the varimax rotation as it maximizes the interpretability of the factors.
@@DataDemystified thanks for quick response , its antecedents and we expect correlation, and my guide asked me to use oblimin but promaz gives clearer pattern .
Also, do you know whats is kappa in promax please?
I just tried bcoz both don't specify non correlations which is the case for my data
@@ankitatibrewal6842 Both rotations should yield very similar results. Again, without seeing the data, it's hard to say. Also, why are you running a factor analysis in the first place? Can you describe the situation more? It's hard to help with such limited information.
how can we conduct factor analysis if we only have dichotomous variables? Or is it's possible?
Tetrachoric correlation matrix should help?
Can you make a video on CATPCA?
Whats the rationale behind using "Correlation Matrix " instead of using "Covariance Matrix" in analysis?
Hi there. If you're referring to the anit-image correlation matrix, we use that to look at the diagonals. We are looking for measures of sampling adequacy at the individual item level (>.5 is considered adequate).
I need a help
You talk too fast.....