For this one above, I say its false since PCA doesn't have clustering. Can someone please confirm this?

ii) T/F: Factor Analysis and Principal Components Analysis have the same objective of modeling the correlation structure in multivariate data.

For this one above, PCA is an exetension of FA, however does this mean this is True? PCA is different from FA, so I think its false

Would greatly appreciate any reply. Tried to put some effort this time. Thanks! ]]>

1) T/F: Common factors estimated using maximum likelihood estimation with a PROMAX rotation are orthogonal.

ANSWER: This is FALSE since PROMAX requires: "With principal component analysis and rotation: You can do an oblique rotation first (oblimin, promax), and examine the component correlation matrix. When should I use rotated component with varimax and when to use maximum likelihood with promax In case of factor analysis?. Available from: https://www.researchgate.net/post/Wh...actor_analysis [accessed May 25, 2017]."

2) T/F: Common factors estimated using Iterated Principal Factor Analysis with a VARIMAX rotation are orthogonal.

ANSWER: This is TRUE since "Varimax rotation is orthogonal rotation in which assumption is that there is no intercorrelations between components." https://www.researchgate.net/post/Wh...actor_analysis

Please advise. I'm confused if this changes anything, but would really appreciate any feedback. Thanks ]]>

Hoping someone more statistically minded can help.

I have a number of variables with different N (they are performance measures and some have been removed due to not understanding the task). I want to bootstrap the correlations but when I do this in SPSS it excludes listwise rather than making use of all the data available (i.e. pairwise). I am wondering if one workaround is to bootstrap each pair of correlations rather than producing the matrix of all variables? My decision on what to include in the regression model would be based on these correlations. So my next but related question is, is different N for the variables a problem for regression?

Many thanks! ]]>