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I have an 18-scale item - Self-Monitoring score, with 10 items loading into Factor A and 5 items into Factor B based on previously established literature. Given that the two factors are already known, using R, how do I calculate the values of Factor A and B by doing factor rotation on the 2 eigenvector values? I'd like to use the two values as separate DVs in a regression.

For example, an average score of the 18 items will be 5, what would the score/value of Factor A vs. B be?

I am new to factor analysis and thought that it may belong to Confirmatory Factor Analysis. I am unsure of the steps needed to take to calculate the final score of the two factors drawing from the 15 items. Thank you!

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    $\begingroup$ Greetings Alicia? What values do you mean? Values can be a lot of things. $\endgroup$ Aug 19, 2022 at 5:37
  • $\begingroup$ Hello Shawn, by values I mean factor scores for factor A and B separately. Thanks! $\endgroup$ Aug 19, 2022 at 19:49
  • $\begingroup$ stats.stackexchange.com/a/126985/3277 is a overview of factor scores computation methods. You will need loadings or factor pattern loadings + factor correlations (in case factors are oblique), and the data. The data might be your sample data while the loadings etc could as well be from literature or previous studies. $\endgroup$
    – ttnphns
    Aug 19, 2022 at 21:26

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