pairwiseMcnemar function

Pairwise McNemar and related tests for Cochran Q test post-hoc

Pairwise McNemar and related tests for Cochran Q test post-hoc

Conducts pairwise McNemar, exact, and permutation tests as a post-hoc to Cochran Q test.

pairwiseMcnemar( formula = NULL, data = NULL, x = NULL, g = NULL, block = NULL, test = "exact", method = "fdr", digits = 3, correct = FALSE )

Arguments

  • formula: A formula indicating the measurement variable and the grouping variable. e.g. y ~ group | block.
  • data: The data frame to use.
  • x: The response variable.
  • g: The grouping variable.
  • block: The blocking variable.
  • test: If "exact", conducts an exact test of symmetry analogous to a McNemar test. If "mcnemar", conducts a McNemar test of symmetry. If "permutation", conducts a permutation test analogous to a McNemar test.
  • method: The method for adjusting multiple p-values. See p.adjust.
  • digits: The number of significant digits in the output.
  • correct: If TRUE, applies a continuity correction for the McNemar test.

Returns

A list containing: a data frame of results of the global test; a data frame of results of the pairwise results; and a data frame mentioning the p-value adjustment method.

Details

The component tables for the pairwise tests must be of size 2 x 2.

The input should include either formula and data; or x, g, and block.

Note

The parsing of the formula is simplistic. The first variable on the left side is used as the measurement variable. The first variable on the right side is used for the grouping variable. The second variable on the right side is used for the blocking variable.

Examples

### Cochran Q post-hoc example data(HayleySmith) library(DescTools) CochranQTest(Response ~ Practice | Student, data = HayleySmith) HayleySmith$Practice = factor(HayleySmith$Practice, levels = c("MowHeight", "SoilTest", "Clippings", "Irrigation")) PT = pairwiseMcnemar(Response ~ Practice | Student, data = HayleySmith, test = "exact", method = "fdr", digits = 3) PT PT = PT$Pairwise cldList(comparison = PT$Comparison, p.value = PT$p.adjust, threshold = 0.05)

References

https://rcompanion.org/handbook/H_07.html

See Also

nominalSymmetryTest, groupwiseCMH, pairwiseNominalIndependence, pairwiseNominalMatrix

Author(s)

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu