In my last post I estimated the point estimates for a logistic regression model using optimx() from the optimx package in R. In this post I would like to contine with this model an try to find the standard error (SE) for the derived estimates.

In my last post I used the optim() command to optimise a linear regression model. In this post, I am going to take that approach a little further and optimise a logistic regression model in the same manner.

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