pairwise.MVA.test: Pairwise permutation tests based on cross (model) validation

In RVAideMemoire: Testing and Plotting Procedures for Biostatistics

Pairwise permutation tests based on cross (model) validation

Description

Performs pairwise comparisons between group levels with corrections for multiple testing, using MVA.test.

Usage

pairwise.MVA.test(X, fact, p.method = "fdr", cmv = FALSE, ncomp = 8,
  kout = 7, kinn = 6, model = c("PLS-DA", "PPLS-DA", "LDA", "QDA",
  "PLS-DA/LDA", "PLS-DA/QDA", "PPLS-DA/LDA","PPLS-DA/QDA"),
  nperm = 999, progress = TRUE, ...)

Arguments

X	a data frame of independent variables.
fact	grouping factor.
p.method	method for p-values correction. See help of p.adjust.
cmv	a logical indicating if the test statistic (NMC) should be generated through cross-validation (classical K-fold process) or cross model validation (inner + outer loops).
ncomp	an integer giving the number of components to be used to generate all submodels (cross-validation) or the maximal number of components to be tested in the inner loop (cross model validation). Can be re-set internally if needed. Does not concern LDA and QDA.
kout	an integer giving the number of folds (cross-validation) or the number of folds in the outer loop (cross-model validation). Can be re-set internally if needed.
kinn	an integer giving the number of folds in the inner loop (cross model validation only). Can be re-set internally if needed. Cannot be > kout.
model	the model to be fitted.
nperm	number of permutations.
progress	logical indicating if the progress bar should be displayed.
...	other arguments to pass to MVA.test.

Details

The function deals with the limitted floating point precision, which can bias calculation of p-values based on a discrete test statistic distribution.

Value

method	a character string indicating what type of tests were performed.
data.name	a character string giving the name(s) of the data.
p.value	table of results.
p.adjust.method	method for p-values correction.
permutations	number of permutations.

Author(s)

Maxime HERVE <[e-mail]>

See Also

MVA.test

Examples

require(pls)
data(mayonnaise)

# PPLS-DA
## Not run: pairwise.MVA.test(mayonnaise$NIR,factor(mayonnaise$oil.type),model="PPLS-DA")

# The function needs a long calculation time!

RVAideMemoire documentation built on Nov. 6, 2023, 5:07 p.m.