653 views

### Can I physically determine the number of factors in Factor Analysis?

I have completed a Factor Analysis on a around 180 responses for a questionnaire with 56 Variables. I got 15 factors using Oblique Rotation PCA. Some of the factors have only two variables of ...
237 views

### Which is more appropriate in this case — PCA or Factor Analysis?

Suppose I have an experiment that has 8 factors. These 8 factors are probably related and can hopefully be reduced. For each combination of these 8 factors that I test, I get a single output. My goal ...
632 views

### Is it necessary to do confirmatory factor analysis for structure equation modelling?

I have done Principal Component Analysis for a scale comprising multiple latent variables. Is it necessary to do Confirmatory Factor Analysis before doing Structure Equation Modelling?
380 views

### What are the differences between these two kinds of PCA?

The book "Elements of Statistical Learning" describes Principal Components Analysis through SVD as follows: $$X = UDV^T$$ Then $UD$ are the Principal Components and $V$ are the directions. ...
487 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, ...
313 views

### How to use factors generated from PCA? [closed]

I have survey data measuring the BIG five personality test. In total, there are 60 variables measuring the five components in a five-point scale. The goal is to look at whether certain experiences in ...
213 views

### How does PCA maximise Total Variance without maximising Co-variance?

https://stats.stackexchange.com/a/3374/92071 - In PCA, the components are actual orthogonal linear combinations that maximize the total variance. In FA, the factors are linear combinations that ...
156 views

### Why does PCA's failure “to explicitly model error variance” make it difficult to interpret components?

I've heard statements like this many times over the years, and it's perhaps expressed most clearly by Preacher & MacCullum (2003), which is a popular paper on stats.stackexchange.com (e.g. ...
152 views

### Principal component analysis (PCA) vs. method of principal components for factor analysis (FA) [duplicate]

I have just read in one of the answers here as follows: One of the biggest reasons for the confusion between the two [principal component analysis (PCA) and factor analysis (FA)] has to do with the ...
122 views

### Conceptual question: how is a factor created in exploratory factor analysis?

As a conceptual question: in exploratory factor analysis, how is a factor created? I would like to know your simple answer to this simple question. Imagine, my academic field does not dependent on ...
I am trying to get into SEM and factor analysis. I understand a factor is a latent construct, say e.g. $intelligence$, user-defined by the (weighted) average of a set of indicators $x_1, x_2\dots x_n$....