I want to fit a weibull regression model. The variables are however given as proportions (i.e. they are in interval <0,1> ... is this compositional data if they do not sum up to 1?). An example would be a proportion of blue balls in the bag or a proportion of patients of a clinic having some health condition.
How can I then interpret the outcome of this regression and is it even OK to fit it as if they were absolute numbers, just with function weibreg for example?
EDIT: To provide more detailed idea about the covariates, I will stick to an easy example with balls and bag. Lets assume we are measuring number of balls of different colours in multiple bags over time. Each bag is measured different number of times, because they came into the study earlier/later. Moreover, each bag has different number of balls in it, some have only under 10, some have more than 1000. Also other variables are measured, such as quality of bag (lets assume this is numeric value, e.g. percentage of cotton ...). Now lets assume that someone punch into each bag every day. Some of them will tear up (=death of bag). I want to model the probability of survival / tearing up , and estimate the effect of colours of balls and other quantities. My first idea was to start by taking only one time point and model time to tear up. In order to have comparable values, I am not using absolute values of numbers of balls of different colours, but rather proportions (3 blue out of 10 are not the same as 3 blue out of 1000). After this simple model I would like to extend my model o longitudinal survival model.