In the Maximum Likelihood Estimator context, I can't find answers for those two questions:
- What are the advantages and disadvantages of estimating of a binary response model with OLS ?
- Same questions but compared to MLE ?
Well if we have a binary model, OLS will just get 0 and 1 and it will not be as precise as if it was more precise value, right ? If we have a big sample, OLS wouldn't be able to show the variety of the different values.
I'm supposed to get a consistent and if possible efficient estimates when I run a model as far as I know.
Well one kicks out average values and the other kick out log(odds). Two completely different types of numbers and not inter-changeable. I think my sample size comment is moot, I was thinking of Poisson regression.