The summary of the logistic regression model produced with the
glm() function has a similar format to that of the linear regression model produced with the
lm() function. This shows us that, for our categorical variables, we have one fewer binary features than the number of levels in the original variable, so for example, the three-valued
THAL input feature produced two binary variables labeled
THAL7. We'll begin by looking first at the regression coefficients that are predicted with our model. These are presented with their corresponding z-statistic. This is analogous to the t-statistic that we saw in linear regression, and again, the higher the absolute value of the z-statistic, the more likely ...