- Thread starter shanehall.m
- Start date
- Tags categorical data chi square exact test post hoc test

I have never heard of a "post hoc" test for fischer. I am not sure what you mean by this, however. Post hoc test in ANOVA say look at whether means at specific levels of an IV vary from each other signficantly on the dependent variable. Fischer does analyze means at all; it commonly is used for nominal data which has no mean. All it tells you is if the variables are associated, not how.

If you have ordinal data, which chi square is sometimes use for there are test like Cramer's V which provide more information. But your data has to be at least ordinal to do this.

If your data is ordinal or interval you probably should not be using Fischer. If it is nominal than I don't think there is anything other than descriptive statistics that compares across the artificial levels of the nominal variable. Certainly you can not use any analysis tied to a mean.

Lastly, you are saying that fishers is only for ordinal data? If it is nominal, the only thing to do is run a chi square test? ...but then what if you violate the chi square assumptions?

If the nominal data violates the chi square assumptions (normally due to sample size or sometimes the structure of your data) than fisher is the way to go. My point is that there is no follow up test as far as I know (I have never seen one mentioned). Fisher (like chi square) only tells you if two variables are related. It does not tell you how, if certain levels of one of the variable differ statistically from another, or the strength of the difference. That is a limiting factor of nominal data.

The only follow up I can think of would be contingency tables - essentially descriptive statistics. I am someone confused about your comments on residual analysis. Fischer does not predict the value of anything - so what are the residuals about? You can't (obviiously) find a discrepancy if you don't predict in the first place.