I am working on finding out whether the patient will develop the disease or not in a hospital.
Might be a basic info but I am just sharing it anyway.
Usually through historic data, I was able to see that patient who was in hospital or the icu for a longer time (more days) did develop the disease.
Similarly if he was in ventilation, it is also an indication of his health status
The distribution of hospital stay and ventilation hours between patients who developed disease and didn't develop disease are different and I verified them visually.
Now my question is
1) Do we need to include these as a predictor (input variable) in our model? I ask because am thinking by using these two variables, model might miss some other input variables which has an influence on outcome. For ex: I may not know whether his urea reading is an indication of whether he will develop disease or not.
Basically what I am trying to know is should we feed variables which we are confident that they will impact the outcome into the model?
Or is the model to help us know something which we aren't aware of .
Can you help me with this?