FSA (version 0.8.30)

dunnTest: Dunn's Kruskal-Wallis Multiple Comparisons.

Description

Performs Dunn's (1964) test of multiple comparisons following a significant Kruskal-Wallis test, possibly with a correction to control the experimentwise error rate. This is largely a wrapper for the dunn.test function in dunn.test. Please see and cite that package.

Usage

dunnTest(x, ...)
# S3 method for default
dunnTest(
  x,
  g,
  method = dunn.test::p.adjustment.methods[c(4, 2:3, 5:8, 1)],
  two.sided = TRUE,
  altp = two.sided,
  ...
)
# S3 method for formula
dunnTest(
  x,
  data = NULL,
  method = dunn.test::p.adjustment.methods[c(4, 2:3, 5:8, 1)],
  two.sided = TRUE,
  altp = two.sided,
  ...
)
# S3 method for dunnTest
print(x, dunn.test.results = FALSE, ...)

Arguments

x

A numeric vector of data values or a formula of the form x~g.

…

Not yet used.

g

A factor vector or a (non-numeric) vector that can be coerced to a factor vector.

method

A single string that identifies the method used to control the experimentwise error rate. See the list of methods in p.adjustment.methods (documented with dunn.test) in dunn.test.

two.sided

A single logical that indicates whether a two-sided p-value should be returned (TRUE; default) or not. See details.

altp

Same as two.sided. Allows similar code with the dunn.test function in dunn.test. two.sided is maintained because it pre-dates altp.

data

A data.frame that minimally contains x and g.

dunn.test.results

A single logical that indicates whether the results that would have been printed by dunn.test function in dunn.test are shown.

Value

A list with three items -- method is the long name of the method used to control the experimentwise error rate, dtres is the strings that would have been printed by the dunn.test function in dunn.test, and res is a data.frame with the following variables:

• Comparison: Labels for each pairwise comparison.

• Z: Values for the Z test statistic for each comparison.

• P.unadj: Unadjusted p-values for each comparison.

• P.adj: Adjusted p-values for each comparison.

Details

This function performs “Dunn's” test of multiple comparisons following a Kruskal-Wallis test. Unadjusted one- or two-sided p-values for each pairwise comparison among groups are computed following Dunn's description as implemented in the dunn.test function from dunn.test. These p-values may be adjusted using methods in the p.adjustment.methods function in dunn.test.

This function is largely a wrapper for the dunn.test function in dunn.test. Changes here are the possible use of formula notation, results not printed by the main function (but are printed in a more useful format (in my opinion) by the print function), the p-values are adjusted by default with the “holm” method, and two-sided p-values are returned by default. See dunn.test function in dunn.test for more details underlying these computations.

References

Dunn, O.J. 1964. Multiple comparisons using rank sums. Technometrics 6:241-252.

See Also

See kruskal.test, dunn.test in dunn.test, posthoc.kruskal.nemenyi.test in PMCMR, kruskalmc in pgirmess, and kruskal in agricolae.

Examples

# NOT RUN {
## pH in four ponds data from Zar (2010)
ponds <- data.frame(pond=as.factor(rep(1:4,each=8)),
                    pH=c(7.68,7.69,7.70,7.70,7.72,7.73,7.73,7.76,
                         7.71,7.73,7.74,7.74,7.78,7.78,7.80,7.81,
                         7.74,7.75,7.77,7.78,7.80,7.81,7.84,NA,
                         7.71,7.71,7.74,7.79,7.81,7.85,7.87,7.91))
ponds2 <- ponds[complete.cases(ponds),]

# non-formula usage (default "holm" method)
dunnTest(ponds2$pH,ponds2$pond)

# formula usage (default "holm" method)
dunnTest(pH~pond,data=ponds2)

# other methods
dunnTest(pH~pond,data=ponds2,method="bonferroni")
dunnTest(pH~pond,data=ponds2,method="bh")
dunnTest(pH~pond,data=ponds2,method="none")

# one-sided
dunnTest(pH~pond,data=ponds2,two.sided=FALSE)

# warning message if incomplete cases were removed
dunnTest(pH~pond,data=ponds)

# print dunn.test results
tmp <- dunnTest(pH~pond,data=ponds2)
print(tmp,dunn.test.results=TRUE)

# }