Hey everyone! I’m currently working on my thesis and want to analyse whether certain health markers have additional value in predicting symptoms to just using an already existing marker . Basically: does variable A explain variance in addition to variable B of variable C?
I analyse two different markers in two different analyses. For one marker, all variables A, B, and C are 5-point Likert, for another marker all variables are on a 0-10 scale.
My supervisor told me I could use multiple linear regression analysis with B as a covariate if my variables are approximately normally distributed so I could simply see if A has additional value in the output. Unfortunately they are not, and even transforming didn’t really help, so now I’m considering ordinal regression analyses.
Now I’m struggling with a few problems:
1. Should I just go for linear regression anyway ?
2. If not, how can I find out whether or not A explains additional variance? I haven’t been able to figure out how to check for it in my R output, but I’ve stumbled upon the likelihood ratio test, could that be an option?
Sorry this is a long read and probably basic stuff, but I’m not super competent in statistics and especially R. I’d really appreciate any sort of feedback!