pairwiseTest function

Wrapper to calculate unadjusted p-values for pairwise comparisons

Calculation of raw p-values for pairwise comparisons of several groups. The data can be split by additional factors. Any test function can be used, that takes two samples x,y as input and returns a list containing the p.value in an element named p.value . The output of this function might be further processed using p.adjust in order to adjust for multiple comparisons.

pairwiseTest(formula, data, by = NULL,
 method = "t.test", control = NULL, ...)

Arguments

• formula: a formula specifiying the response and the factor variable: response ~ factor
• data: a data frame, containing the variables specified in formula
• by: optional vector of character strings, defining factors by which to split the data set. Then, pairwise comparisons are performed separately for each level of the specified factors.
• method: character string, giving the name of the function, which shall be used to calculate local p-values. Any function, taking two vectors x, and y as first arguments and returning a list with the p.value in a list element named p.value can be specified.
• control: optional character string, defining the name of a control group. Must be one of the levels of the factor variable defined in formula . By default control=NULL, then all pairwise comparisons between the levels of the factor variable are computed.
• ...: Arguments to be passed the function defined in method

Details

This function splits the response variable according to the factor(s) specified in by , and within each subset according to the grouping variable specified in formula . The function specified in method is called to calculate a p.value for all pairwise comparisons of between the subsets, within each level of by . The p-values are NOT adjusted for multiple hypothesis testing.

For binomial proportions, only "Prop.test" can be specified in the argument method ; For continous variables, any function can be specified, which takes x and y as first arguments, and returns a list containing a list containing the appropriate p-value in the element named p.value

(as do the functions of class "htest" ). See the examples for details.

Returns

A named list with elements - byout: a list, containing the output of pairwiseTestint for each level of by, i.e. a data.frame containing with columns p.value ,compnames groupx , groupy

• bynames: a character vector containing the names of the levels of the factors specified in by

• method: a character string, name of the function used

• control: a character string

• by: vector of character strings, same as argument by

• ...: further arguments that were passed to FUN

Author(s)

Frank Schaarschmidt

See Also

You can use summary.pairwiseTest to calculate multiplicity adjusted p-values from the output of pairwiseTest.

The following methods provide multiplicity adjusted p-values for various situations: pairwise.t.test, pairwise.prop.test, \link{p.adjust} , summary.glht(multcomp) , simtest.ratio(mratios)

Examples

#######################################################
# The rooting example:
# Calculate confidence intervals for the 
# difference of proportions between the 3 doses of IBA,
# separately for 4 combinations of "Age" and "Position".
# Note: we pool over Rep in that way. Whether this makes
# sense or not, is decision of the user.

data(rooting)

# Pairwise Chi-square tests:

aproots<-pairwiseTest(cbind(root, noroot) ~ IBA,
 data=rooting, by=c("Age", "Position"), method="Prop.test")

aproots

# With Holm adjustment for multiple hypotheses testing:

summary(aproots, p.adjust.method="holm")

#########################################################

data(Oats)

apc <- pairwiseTest(yield ~ nitro, data=Oats,
 by="Variety", method="wilcox.test")

apc

summary(apc)
summary(apc, p.adjust.method="holm")