I am working on a model based on logistic regression with a binary response variable and my data consists of ratios of integers (number of positive observations out of the total number of observations).
I am trying to speed up the regression by downsampling the ratios (I have to run it on a massive amount of datasets). I can estimate the minimum number of observations (the denominator of a ratio) that I need to perform the required test at a specific power. So I am wondering if
- downsampling is a valid way to speed up the regression?
- If so, what is an appropriate way to do this? Can I just, say, pick a random number from Binomial(20, 0.25) if I want to downsample a ratio 250/1000 (=0.25)?
I hope my question is clear. I have just started learning stats so I apologize for this naive question.