How to identify if there is a relationship between 5 categorical independent variables to a binary dependent variable? My dataset has 5 independent variables, each with a value of either Large, Medium or None and a binary dependent variable. The dataset has 67 rows with a split of 17:50.
I would like to identify if there is a relationship between the independent variables and the dependent variable and to explore which variables/set of variables have the largest impact on the result.
Most of the solutions I have checked so far (Nominal Variable Association and Cramér's V) don't support more than one independent variable.
One simple, tricky but probably best approach would be using a Decision Tree. After building a model, you can analyze the structure of the tree to identify the relation. Afterward, you can list the feature importance to see the effect of an independent variable on the dependent variable.
In python, you can use sklearn to achieve it. feature_importances_ will give you Gini's importance of the features and the plot_tree() function to see the structure of the tree. This article might also help to see how to do that.