I have been scratching my head for some time when it comes to analyzing trial data where the outcome variable is a component of another important outcome variable that is affected by the intervention.
In my example, we have conducted a double-blind weight loss trial with two groups. The intervention leads to a significantly lower total body weight vs. controls.
What I am now stuck thinking about is how to model various aspects of body composition (i.e., fat mass and fat free mass) which are components of total body weight.
In the same way that fat mass and fat free mass makes up total body weight, total body weight loss will be composed of fat mass and fat free mass loss. I am therefore thinking that when modeling the effect of the intervention on e.g., fat mass, these models should be adjusted for total body weight.
An option would be to use body fat percentage as the outcome variable. However, the range of body fat percentage is quite narrow as 100 percent body fat is physiologically impossible).
Happy to hear your thoughts about this. Should outcome models with body composition data, e.g., body fat, be adjusted for total body weight when we know that there is an effect of the intervention on total body weight?