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.

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.

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