PMCMRplus: manyOneUTest – R documentation

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PMCMRplus

manyOneUTest

Multiple Comparisons with One Control (U-test)

Description

Performs pairwise comparisons of multiple group levels with one control.

Usage

manyOneUTest(x, ...)

## Default S3 method:
manyOneUTest(
  x,
  g,
  alternative = c("two.sided", "greater", "less"),
  p.adjust.method = c("single-step", p.adjust.methods),
  ...
)

## S3 method for class 'formula'
manyOneUTest(
  formula,
  data,
  subset,
  na.action,
  alternative = c("two.sided", "greater", "less"),
  p.adjust.method = c("single-step", p.adjust.methods),
  ...
)

Arguments

`x`	a numeric vector of data values, or a list of numeric data vectors.
`...`	further arguments to be passed to or from methods.
`g`	a vector or factor object giving the group for the corresponding elements of `"x"`. Ignored with a warning if `"x"` is a list.
`alternative`	the alternative hypothesis. Defaults to `two.sided`.
`p.adjust.method`	method for adjusting p values (see `p.adjust`)
`formula`	a formula of the form `response ~ group` where `response` gives the data values and `group` a vector or factor of the corresponding groups.
`data`	an optional matrix or data frame (or similar: see `model.frame`) containing the variables in the formula `formula`. By default the variables are taken from `environment(formula)`.
`subset`	an optional vector specifying a subset of observations to be used.
`na.action`	a function which indicates what should happen when the data contain `NA`s. Defaults to `getOption("na.action")`.

Details

This functions performs Wilcoxon, Mann and Whitney's U-test for a one factorial design where each factor level is tested against one control (m = k -1 tests). As the data are re-ranked for each comparison, this test is only suitable for balanced (or almost balanced) experimental designs.

For the two-tailed test and p.adjust.method = "single-step" the multivariate normal distribution is used for controlling Type 1 error and to calculate p-values. Otherwise, the p-values are calculated from the standard normal distribution with any latter p-adjustment as available by p.adjust.

Value

A list with class "PMCMR" containing the following components:

method: a character string indicating what type of test was performed.
data.name: a character string giving the name(s) of the data.
statistic: lower-triangle matrix of the estimated quantiles of the pairwise test statistics.
p.value: lower-triangle matrix of the p-values for the pairwise tests.
alternative: a character string describing the alternative hypothesis.
p.adjust.method: a character string describing the method for p-value adjustment.
model: a data frame of the input data.
dist: a string that denotes the test distribution.

References

OECD (ed. 2006) Current approaches in the statistical analysis of ecotoxicity data: A guidance to application, OECD Series on testing and assessment, No. 54.