Support Fisher exact test reporting about report

[rempsyc]

Hi Christophe! Thanks so much for opening an issue!

We will most likely one day get to this issue but given that we have a rather large back-log, it may take some time to get to it. So to answer your other email questions, eventually hopefully more methods will be supported, but having this specific issue opened will help us prioritize the Fisher exact test specifically.

And yes, we do accept new contributors for new methods. In fact, we also invite you and anyone to contribute to easystats and report. Doing so will significantly speed up the adopting of the desired changes. Please see the contributor guidelines here:

https://easystats.github.io/report/CONTRIBUTING

The general workflow is the following:

1. Create a fork of this repository
2. Create a new branch specific to the change you want to make (e.g., branch_fischer)
3. Make the changes locally on that branch on your PC
4. When satisfied, push the changes to GitHub (to your branch/fork)
5. Then you will have a pop-up asking if you want to submit a Pull Request (PR), say yes.
6. In the PR, explain your changes.
7. Then, we will assign reviewers to check your changes, and if it satisfies the requirement, we will accept it.
8. Normally, you will then become a contributor.

Team, have I forgotten anything?

Let me know if you have any question. Thanks!

[rempsyc]

Regarding this specific issue, here's a reprex for future reference:

# load packages
library(easystats)

# Create data and fischer test object
TeaTasting <-
  matrix(c(3, 1, 1, 3),
         nrow = 2,
         dimnames = list(Guess = c("Milk", "Tea"),
                         Truth = c("Milk", "Tea")))
x <- fisher.test(TeaTasting, alternative = "greater")

# report doesn't work
report(x)
#> Error: This test is not yet supported. Please open an issue at
#>   https://github.com/easystats/report/issues.

# parameters work
parameters(x)
#> Fisher's Exact Test for Count Data
#> 
#> Odds Ratio |      95% CI |     p
#> --------------------------------
#> 6.41       | [0.31, Inf] | 0.243
#> 
#> Alternative hypothesis: true odds ratio is greater than 1

# effectsize works
interpret_cramers_v(effectsize(x))
#> Cramer's V (adj.) |       95% CI | Interpretation
#> -------------------------------------------------
#> 0.35              | [0.00, 1.00] |          large
#> 
#> - One-sided CIs: upper bound fixed at [1.00].
#> - Interpretation rule: funder2019

^{Created on 2023-03-23 with reprex v2.0.2}

As you can see, although you can't use report on a Fischer exact test object, you can for the moment extract the parameters and effect size.