vanWaerdenAllPairsTest function

van-der-Waerden's All-Pairs Comparison Normal Scores Test

van-der-Waerden's All-Pairs Comparison Normal Scores Test

Performs van-der-Waerden all-pairs comparison normal scores test.

vanWaerdenAllPairsTest(x, ...) ## Default S3 method: vanWaerdenAllPairsTest( x, g, p.adjust.method = c("single-step", p.adjust.methods), ... ) ## S3 method for class 'formula' vanWaerdenAllPairsTest( formula, data, subset, na.action, 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.
  • 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 NAs. Defaults to getOption("na.action").

Returns

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.

Details

For all-pairs comparisons in an one-factorial layout with non-normally distributed residuals van-der-Waerden's normal scores transformation can be used prior to an all-pairs comparison test. A total of m=k(k1)/2m = k(k-1)/2

hypotheses can be tested. The null hypothesis Hij:Fi(x)=Fj(x)_{ij}: F_i(x) = F_j(x) is tested in the two-tailed test against the alternative Aij:Fi(x)Fj(x),  ij_{ij}: F_i(x) \ne F_j(x), ~~ i \ne j. For p.adjust.method = "single-step" the Tukey's studentized range distribution is used to calculate p-values (see Tukey). Otherwise, the t-distribution is used for the calculation of p-values with a latter p-value adjustment as performed by p.adjust.

References

Conover, W. J., Iman, R. L. (1979) On multiple-comparisons procedures, Tech. Rep. LA-7677-MS, Los Alamos Scientific Laboratory.

van der Waerden, B. L. (1952) Order tests for the two-sample problem and their power, Indagationes Mathematicae 14 , 453--458.

See Also

vanWaerdenTest, vanWaerdenManyOneTest, normOrder.

  • Maintainer: Thorsten Pohlert
  • License: GPL (>= 3)
  • Last published: 2024-09-08

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