I performed a correlation analysis on my IVs to see which are related. As this is data from an experiment, I also have variables that are in general not so easy to capture from people in real life without a questionnaire. So I was wondering if there's a chance that I can combine a set of (highly correlated) variables to replace another variable.
For example, variable A is correlated with variables B, C, D, E. Could I somehow create a replacement for variable A by combining variables B,C, D, and E?
I know that a factor analysis is able to do this, but I believe this wouldn't work in my case. Performing a factor analysis on my the example that I provided, would need variable A to be included, while I want to find a way to exclude it. Or am I wrong here and is factor analysis the right approach.
Best Answer
You can try regressing A in terms of B, C, D and E and then use that equation rather than the exact 'A' value
You might want to give Structural Equation Modelling a go. This Introduction to structural equation modeling gives you a lot of references and links to get started on.