Solved – How to report Fisher’s Exact Test

fishers-exact-testreportingspss

I have used Fisher's Exact rather than Chi-square due to having some cells with small sample sizes, but I have no clue how to report this? In the output, I am given the Fisher's test value (14.510) and the statistical significance (.042) That's it – no df etc.

As I would usually report a chi square test as x2 (df, n=participants) = 14.510, p=.042 along with a phi or cramer's v value, how would you suggest I report the results for a Fisher's Exact Test?

Finally, would I still report Phi/Cramer's V?

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I am not familiar with the Fisher's test output in SPSS, but in other computing software's you will receive things like test-statistics, p-values, confidence intervals, and odds ratios.

I think odds ratios are a good thing to report because it will show the difference between the groups you are looking at (and maybe the confidence interval of the odds ratio). I think generally, it depends on who you are reporting to. If you are reporting to more math literate people, the more information about the test (even your SPSS output) is satisfactory. However, otherwise I would simply tell them that based on the data you were given (and the low p-value) that there is significant evidence that the groups (or whatever you are testing) differ from one another -- and you can mention in what direction.

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Solved – Fisher’s exact test in 3×2 contingency table

It sounds like you are asking a lot of different questions here.

My question is: how should I interpret the p value? I don't understand what is that referred to.

The null hypothesis for Fisher's Exact test is that the groups do not affect the outcome, i.e. that they are independent. Rejection of the null hypothesis indicates the outcome (a, b, or c) is dependent on group.

fisher.test(matrix(c(2, 12, 1, 5, 3, 1), 
            nrow=2, ncol=3, byrow=TRUE))
Fisher's Exact Test for Count Data

data:  dta
p-value = 0.05082
alternative hypothesis: two.sided

In this case your $p$ value is approximately 0.05082. I will let you decide whether to reject the null.

Having the p value, how can I say that one of the three forms is statistically significant more represented than the others (if true)?

This is a separate question and I'm not sure what you are trying to ask.

Solved – Fisher’s exact test

The massive 58 amid much lower frequencies signals that any test is just quantifying a major failure of independence. I did this in Stata. The command ret li (short for return list) obliges Stata to show results as exactly as it knows them, but both tests yield P-values that are 0.000 to 3 d.p. It is right to be a little cautious about low expected values (for row 1 here in particular) but the test results are overwhelming.

. tabi 0  2 \ 5 58 \ 4 3 \ 4 3 

            |          col
        row |         1          2 |     Total
 -----------+----------------------+----------
          1 |         0          2 |         2 
          2 |         5         58 |        63 
          3 |         4          3 |         7 
          4 |         4          3 |         7 
 -----------+----------------------+----------
      Total |        13         66 |        79 

      Pearson chi2(3) =  20.5779   Pr = 0.000

. ret li 

scalars:
              r(p) =  .0001288081813192
           r(chi2) =  20.57794057794058
              r(c) =  2
              r(r) =  4
              r(N) =  79

. tabi 0  2 \ 5 58 \ 4 3 \ 4 3 , exact

Enumerating sample-space combinations:
stage 4:  enumerations = 1
stage 3:  enumerations = 3
stage 2:  enumerations = 17
stage 1:  enumerations = 0

             |          col
         row |         1          2 |     Total
  -----------+----------------------+----------
           1 |         0          2 |         2 
           2 |         5         58 |        63 
           3 |         4          3 |         7 
           4 |         4          3 |         7 
  -----------+----------------------+----------
       Total |        13         66 |        79 

       Fisher's exact =                 0.000

. ret li 

scalars:
        r(p_exact) =  .0003124258226793
              r(c) =  2
              r(r) =  4
              r(N) =  79

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Solved – Fisher’s exact test in 3×2 contingency table

Solved – Fisher’s exact test

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