Linked Questions
12 questions linked to/from Where is the indeterminacy of factor values on this plot explaining factor analysis?
266
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What are the differences between Factor Analysis and Principal Component Analysis?
It seems that a number of the statistical packages that I use wrap these two concepts together. However, I'm wondering if there are different assumptions or data 'formalities' that must be true to use ...
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4
answers
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How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
Canonical correlation analysis (CCA) is a technique related to principal component analysis (PCA). While it is easy to teach PCA or linear regression using a scatter plot (see a few thousand examples ...
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41
votes
2
answers
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How does Factor Analysis explain the covariance while PCA explains the variance?
Here is a quote from Bishop's "Pattern Recognition and Machine Learning" book, section 12.2.4 "Factor analysis":
According to the highlighted part, factor analysis captures the covariance between ...
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24
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1
answer
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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 ...
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2
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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 ...
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1
answer
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Data space, variable space, observation space, model space (e.g. in linear regression)
Suppose we have the data matrix $\mathbf{X}$, which is $n$-by-$p$, and the label vector $Y$, which is $n$-by-one. Here, each row of the matrix is an observation, and each column corresponds to a ...
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14
votes
2
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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 ...
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2
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Difference between loadings and correlations between observed variables and factor saved scores in factor analysis
I thought that the loadings in factor analysis were the correlations between the observed variables and the latent factors. However, when I do factor analysis in R using the psych package, this does ...
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2
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1
answer
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Orthogonality of the basis in factor analysis
I have been studying principal component analysis (PCA) and then I have gone up to factor analysis (FA). I understood that PCA seeks orthonormal basis, but I am not so sure if this is the case for ...
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4
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1
answer
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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, ...
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4
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1
answer
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Factor extraction methods: Harris and Image extraction
Is Harris's (1962) extraction method considered a form of principal component analysis (PCA) or factor analysis (FA)? What about image extraction?
I am using SAS and the documentation says:
HARRIS | ...
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0
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Can I include new items into an existing exploratory factor analysis?
I have a panel dataset from a survey before and after an intervention. One question is a Q-method-style question where students have been sorting statements about the type of teaching they receive.
In ...
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