Correct approach for nominal analysis

I have a dataset with 4 columns of nominal/categorical data. I would like to assess if 3 of the columns either individually or in combination impact on the 4th. I know I have seen a chi square/contingency table approach years of in Orange but wondered what approach to take in Knime.
The data has country, relationship, event type and employment, and I need to see if the employment type is influenced by any of the other data. I know that there are individual statistical differences between country and employment, and event type and employment but it is the interplay of these I would like to identify from the data.

Any hints or advice?

It seem something close

node is doing.

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The cross tab does a two factor contingency table, but not multiple. So it will let me test each individual dimension, but not the layered possibilities. I might dig out Orange again then see if I can get my head around the specific terms used and reference back.

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