my question is related to this post using glm for logistic regression and scaling. My question is, why in the solution proposed by @gung - Reinstate Monica the chi-squared statistic obtained from the likelihood ratio test is then divided by the degrees of freedom?
A different way to visualize variable importance with a mix of categorical and continuous variables is to get a variable's chi-squared statistic from its likelihood ratio test and divide that by its degrees of freedom.