I have a question about the accepted/most efficient type-casting to format the covariates in a linear or logistic regression.

I see that covariates accepts a list of Float64Expression.

I have a mixture of int/float covariates and categorical (non-dichotomous) covariates. I have converted each categorical trait into a series of dichotomous dummy variables.

Is this the best way to handle these variables? Or is it better to pass them as an int where each integer is a different factor? Or is it possible to pass these variables in the original string format?

For one of my runs I got a “Error summary: HailException: Failed to fit logistic regression null model (standard MLE with covariates only): exploded at Newton iteration 10” error, and I’m worried the increase in the # of covariates due to the expansion of categorical variables into several dummy variables was a factor in the regression not converging.