In SPSS, when performing binary logistic regression using multiple categorical predictors, a significance level is detailed for the variable overall in addition to each category. This strikes me as useful as the model is built up as the addition of a predictor may negate the effect of previously added variables. What is this overall significance a measure of?
In R, the summary of my GLMs do not include this information. As I am building models I can anova(model0, model1) to test the impact of a new addition. However, how would one then detect if a previous predictor had become insignificant overall? Is the significance of a single category sufficient to warrant inclusion?
I have read the following article which was helpful: