Say you have IQ and Academic Achievement (AA) and you create a partial correlation with both of those variables and covary them with Socioeconomic Status (SES).
From this video ( https://www.youtube.com/watch?v=GUNPXLRk_60 ), I learned that, if you want to graph that partial regression in SPSS, then you can use the residuals of two regressions, IQ with SES and AA with SES.
Thus, if I am understanding this correctly, the residual of each of those regressions is the value of the dependent variables (IQ and AA) controlled for SES, correct?
This leads me to my current question. Can you control for variables in a linear discriminant analysis? In SPSS, there is no option to, which makes sense because of the nature of the classification function. However, what if I regressed each of the individual dependent variables in the LDA on typical covariates, such as age, sex, and race, then used those residuals of the dependent variables for the discriminant function?
Would that technically control for the variables or is there some problem with this that I am not seeing?