I am trying to run a binomial regression on a dataset of groups that have taken a pass/fail test. I am working in Python, with statsmodels. My dependent variable is a 2x array of the number of successes and failures for each group. There are eight features, all of which are percentages. For each group in the dataset, the percentages for the eight features will add up to 1.
When I run the binomial regression, all of the coefficients come back as negative, which I don't understand. How can I interpret this? It can't be that every possible feature makes success less likely for this group. Surely at least one of them should be positive? I was hoping to find out which factors increased the success rate, but I can't tell that from my results ... can I?
I tried to add a constant, but the results were still uniformly negative. I also tried normalizing the data, but that had almost not effect. I am very new to this, so I'm not sure if I am doing the regression wrong, or if I am doing it right but just don't know how to interpret the results. Your advice will be appreciated!