I am trying to run a logistic regression on a data set where my dependent variable is a proportion of a binary variable, rather than the binary variable itself. I have seen a ton of documentation that says this is possible, but I am having trouble finding an example of how to actually do it. I am open to using scikit learn, statsmodels, or any other library that will do it.
I have added a photo showing a simplified version of my data.
successes here is just a count of a binary (1/0) outcome. instead of having the individual observations, I only have them rolled up, but my understanding is that it is still a logistic regression problem. I want to predict the dependent variable 'proportion' based on the features. I understand this conceptually, but am just trying to find an example of this in python. all of the examples I have seen assume a binary dependent variable.
your help is appreciated!