Choosing variabilities

Hi all, I am trying to model a system and I am running into the issue of which parameters should I include variabilities. The model is complex with more than 6-7 parameters and its a dose driven effect model, fitting the effect observations only. Some parameters describe the dose dynamics and other contribute to effect. Leaving aside the variabilities on effect part if I concentrate on dose part variabilites, it leaves me in a puzzle. What dose parameters should I choose to add variability on. There is very little physiological or mechanistic information on the dose part, which may also be called a hypothesis. I chose different models with variabilities on different dose parameters. Almost all run with different end OBJ function. The final fit is more or less similar between most of the models. It's like parameter values change but they compensate each other in final effect. Now, my puzzle is, which model (with which variabilities) should I choose. The one with best OBJ func. The one that may make some physiological relevance (although this relevance may get refuted). Any insight into experience with such problems would be helpful. Thanks, Pratik Bhagunde