How to test if IV and DV measuring different things


After working around a year on my research paper I recieved a critic from one of my colleagues that question my whole research designe. Since I’m not an expert, I wanted to ask if his critic is fair and is there a way to go about it.

I’m trying to use a GLMM model to measure the assoication of a some number of variables with the success of musicians. I collected my data from online music platforms such as Discogs. The data includes information about live performances and releases. I use number of live performances as the success indicator (DV). Using this data I construct a panel where
observations is the representation of an artist’s career at different point in time.

The potential problem is that a number of my IVs are also based on the live performances. For example number of peers that appear on the same lineup (measure of exposure), number of music venues and cities that she performed, and etc. That is, both DVs and IVs. are constructed from the same observational data and therefore they might capture the same construct instead of two distinct ones. As my colleagues put it: “ofcourse having those with larger number of live performances are more likely to get bookings in larger number cities and venues, and appear in lineups with more diverse set of artists”.

my question is: is it a fair critic? if yes, is there anyway to go about it? if not, is there any test to support my argument?

For general non-health-related stats questions go to