## When you want more than a chi-squared test, consider a measure of association

In my last post, I made the point that p-values should not necessarily be considered sufficient evidence (or evidence at all) in drawing conclusions about associations we are interested in exploring. When it comes to contingency tables that represent the outcomes for two categorical variables, it isn’t so obvious what measure of association should augment (or replace) the \(\chi^2\) statistic.
I described a model-based measure of effect to quantify the strength of an association in the particular case where one of the categorical variables is ordinal.
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