Hi all
I know there are few methods to estimate a logistic regression when the binary dependant variable has rare events (very few ones relative to many zeros).
In a draft of my paper, I showed results using a standard probit model. I was then advised by the reviewer to show robustness of my results after considering the fact that the event is very rare.
The problem is that I prefer to be consistent and use a probit model rather than a loigit model but as far as I can see the only available ones are those of logit such as
.
Does anyone have more information regarding this?
Thanks
I know there are few methods to estimate a logistic regression when the binary dependant variable has rare events (very few ones relative to many zeros).
In a draft of my paper, I showed results using a standard probit model. I was then advised by the reviewer to show robustness of my results after considering the fact that the event is very rare.
The problem is that I prefer to be consistent and use a probit model rather than a loigit model but as far as I can see the only available ones are those of logit such as
Code:
firthlogit or relogit
Does anyone have more information regarding this?
Thanks
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