Linked Questions

33
votes
1answer
40k views

What is the intuitive reason behind doing rotations in Factor Analysis/PCA & how to select appropriate rotation?

My Questions What is the intuitive reason behind doing rotations of factors in factor analysis (or components in PCA)? My understanding is, if variables are almost equally loaded in the top ...
20
votes
2answers
35k views

Methods to compute factor scores, and what is the “score coefficient” matrix in PCA or factor analysis?

As per my understanding, in PCA based on correlations we get factor (= principal component in this instance) loadings which are nothing but the correlations between variables and factors. Now when I ...
19
votes
2answers
14k views

PCA and exploratory Factor Analysis on the same dataset: differences and similarities; factor model vs PCA

I would like to know if it makes any logical sense to perform principal component analysis (PCA) and exploratory factor analysis (EFA) on the same data set. I have heard professionals expressly ...
17
votes
1answer
16k views

What is the proper association measure of a variable with a PCA component (on a biplot / loading plot)?

I am using FactoMineR to reduce my data set of measurements to the latent variables. The variable map above is clear for me to interpret, but I am confused when ...
10
votes
2answers
13k views

In Factor Analysis (or in PCA), what does it mean a factor loading greater than 1?

I've just run a FA using a oblique rotation (promax) and an item yielded a factor loading of 1.041 on one factor, (and factor loadings of -.131, -.119 and .065 on the other factors using pattern ...
12
votes
2answers
3k views

Sum of rating scores vs estimated factor scores?

I'd be interested to receive suggestions about when to use "factor scores" over plain sum of scores when constructing scales. I.e. "Refined" over "non-refined" methods of scoring a factor. From ...
6
votes
5answers
2k views

Clustering of variables: but they are mixed type, some are numeric, some are categorical

I have a dataset with 15 variables. Some variables are numeric, continuous. Other variables are boolean, dichotomous (true/false). There's also one variable categorical, nominal. ...
8
votes
0answers
2k views

Cluster analysis vs Factor analysis as a means for “grouping” variables or cases: the differences

I've noticed responses that at face value seem to be in contradiction with each other. For instance, here @peter-flom writes Short answer: Cluster analysis is about grouping subjects (e.g. ...
0
votes
1answer
2k views

PCA with oblimin rotation: should I interpret component matrix, pattern matrix or structure matrix?

I conducted a principal component analysis (PCA) with direct oblimin factor rotation in SPSS. Because by that time I didn't know any better, I used the COMPONENT MATRIX for interpretation. I added ...
2
votes
1answer
380 views

A textbook error w.r.t structure and pattern loadings

I have this picture in Lattin representing structure and pattern loadings in factor analysis. If $Z$ (an observed variable) $=w_1 F_1+w_2 F_2$ (according to factor model), then the pattern loadings of ...
3
votes
1answer
469 views

Understanding (exploratory) factor analysis: some points for clarification

[A question about what we optimize in FA, is FA a clustering of variables, and when/how we choose the number of factors] I have read some tutorials and looked at some of the questions here, as well, ...
2
votes
1answer
30 views

Why is computation of scores in Sparse PCA different from T=XP?

I am recently learning Sparse PCA. From a lately published paper All sparse PCA models are wrong, but some are useful. Part I: Computation of scores, residuals and explained variance I learned that ...