Extending my previous question ( Multiple regression with correlated variables ), can I do multiple regression with height, weight, waist, BMI (body mass index) and BSA (body surface area) as predictor variables on a health variable (yvar) in a large data set (N=about 7000)? Obviously, BMI and BSA are derived from height and weight, but I want to find out if correlation is greater for BMI or BSA (so that they may be better to use for prediction) than for height and weight. Will the results be valid or is there some major limitation?
Edit: The regression runs without any error and shows that height, weight and BSA are significant predictors of yvar but waist and BMI are not significant predictors.