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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