pairwiseNominalIndependence function

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.

Returns

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.

Examples

### Independence test for a 4 x 2 matrix
data(Anderson)
fisher.test(Anderson)
Anderson = Anderson[(c("Heimlich", "Bloom", "Dougal", "Cobblestone")),]
PT = pairwiseNominalIndependence(Anderson,
                                 fisher = TRUE,
                                 gtest  = FALSE,
                                 chisq  = FALSE,
                                 cramer = TRUE)
PT                                
cldList(comparison = PT$Comparison,
        p.value    = PT$p.adj.Fisher,
        threshold  = 0.05)

References

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

See Also

pairwiseMcnemar, groupwiseCMH, nominalSymmetryTest, pairwiseNominalMatrix

Author(s)

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu