Combing variables with computed variable f(x)
Posted: Thu Apr 07, 2022 7:35 am
I want to combine two 2 variables, 'vegetables eaten' (1 = low vegetable intake, 7 = high vegetable intake )and 'junk food eaten', (1= low junk food intake, 10= high junk food intake) into one predictor variable called 'physical health'. By the way I can't change how these variables are set up.
Now, obviously the higher 'vegetables eaten' is, the higher physical health should be. And, the lower 'junk food eaten' is, the higher physical health should be, and that's the problem I'm having.
I've tried computing a new variable with the function: vegetables * (1 / junkfood), but this gives a very low end bias. When you look at the distribution of scores for this new variable, it shows my sample has an on average bad physical health when in reality, when you look at a density plot for both vegetables and junk food individually, on average people eat a decent amount of vegetables and very little junk food.
Need help coming up with a suitable function for my combined predictor variable, 'physical health'.
Now, obviously the higher 'vegetables eaten' is, the higher physical health should be. And, the lower 'junk food eaten' is, the higher physical health should be, and that's the problem I'm having.
I've tried computing a new variable with the function: vegetables * (1 / junkfood), but this gives a very low end bias. When you look at the distribution of scores for this new variable, it shows my sample has an on average bad physical health when in reality, when you look at a density plot for both vegetables and junk food individually, on average people eat a decent amount of vegetables and very little junk food.
Need help coming up with a suitable function for my combined predictor variable, 'physical health'.