Pairwise tests of independence for nominal data

Conducts pairwise tests for a 2-dimensional matrix, in which at at least one dimension has more than two levels, as a post-hoc test. Conducts Fisher exact, Chi-square, or G-test.

Usage

pairwiseNominalIndependence(
  x,
  compare = "row",
  fisher = TRUE,
  gtest = TRUE,
  chisq = TRUE,
  method = "fdr",
  correct = "none",
  yates = FALSE,
  stats = FALSE,
  cramer = FALSE,
  digits = 3,
  ...
)

Arguments

x: A two-way contingency table. At least one dimension should have more than two levels.
compare: If "row", treats the rows as the grouping variable. If "column", treats the columns as the grouping variable.
fisher: If "TRUE", conducts fisher exact test.
gtest: If "TRUE", conducts G-test.
chisq: If "TRUE", conducts Chi-square test of association.
method: The method to adjust multiple p-values. See stats::p.adjust.
correct: The correction method to pass to DescTools::GTest.
yates: Passed to correct in stats::chisq.test.
stats: If "TRUE", includes the Chi-square value and degrees of freedom for Chi-square tests, and the G value.
cramer: If "TRUE", includes an effect size, Cramer's V in the output.
digits: The number of significant digits in the output.
...: Additional arguments, passed to stats::fisher.test, DescTools::GTest, or stats::chisq.test.

Value

A data frame of comparisons, p-values, and adjusted p-values.

Acknowledgments

My thanks to Carole Elliott of Kings Park & Botanic Gardens for suggesting the inclusion on the chi-square statistic and degrees of freedom in the output.

References

https://rcompanion.org/handbook/H_04.html

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Examples

### Independence test for a 4 x 2 matrix
data(Anderson)
fisher.test(Anderson)
#> 
#> 	Fisher's Exact Test for Count Data
#> 
#> data:  Anderson
#> p-value = 0.000668
#> alternative hypothesis: two.sided
#> 
Anderson = Anderson[(c("Heimlich", "Bloom", "Dougal", "Cobblestone")),]
PT = pairwiseNominalIndependence(Anderson,
                                 fisher = TRUE,
                                 gtest  = FALSE,
                                 chisq  = FALSE,
                                 cramer = TRUE)
PT                                
#>               Comparison p.Fisher p.adj.Fisher Cramer.V
#> 1       Heimlich : Bloom 0.740000      0.74000   0.0475
#> 2      Heimlich : Dougal 0.013100      0.02620   0.3930
#> 3 Heimlich : Cobblestone 0.000994      0.00596   0.4980
#> 4         Bloom : Dougal 0.037600      0.05640   0.3530
#> 5    Bloom : Cobblestone 0.003960      0.01190   0.4600
#> 6   Dougal : Cobblestone 0.720000      0.74000   0.1160
cldList(comparison = PT$Comparison,
        p.value    = PT$p.adj.Fisher,
        threshold  = 0.05)                             
#>         Group Letter MonoLetter
#> 1    Heimlich      a        a  
#> 2       Bloom     ab        ab 
#> 3      Dougal     bc         bc
#> 4 Cobblestone      c          c