Description Usage Arguments Details Value Note See Also Examples
Tests for significant differences among all pairs of populations in a chi-square test, correcting for multiple comparisons.
1 2 3 4 5 6 7 8 | chisq.post.hoc(
tbl,
test = c("fisher.test"),
popsInRows = TRUE,
control = c("fdr", "BH", "BY", "bonferroni", "holm", "hochberg", "hommel"),
digits = 4,
...
)
|
tbl |
A |
test |
What sort of test will be used? This must have an object called p.value so it can correct the p-values. Defaults to "fisher.test" |
popsInRows |
A logical indicating whether the populations form the rows
(default; |
control |
A string indicating the method of control to use. See details. |
digits |
A numeric that controls the number of digits to print. |
... |
Other arguments sent to whatever test the user specifies. |
Post-hoc tests for which pairs of populations differ following a significant
chi-square test can be constructed by performing all chi-square tests for all
pairs of populations and then adjusting the resulting p-values for inflation
due to multiple comparisons. The adjusted p-values can be computed with a
wide variety of methods – fdr, BH, BY, bonferroni, holm, hochberg, and
hommel. This function basically works as a wrapper function that sends the
unadjusted “raw” p-values from each pair-wise chi-square test to the
p.adjust
function in the base R program. The p.adjust
function
should be consulted for further description of the methods used.
A data.frame with a description of the pairwise comparisons, the raw p-values, and the adjusted p-values.
This code was adapted and modified from the NCStats package
chisq.test
and p.adjust
.
1 2 3 4 5 6 |
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