NPC: NonParametric Combination of Test Statistic
In SOUP: Stochastic Ordering Using Permutations (and Pairwise Comparisons)

Description Usage Arguments Details Value Note Author(s) References See Also

NonParametric Combination of the test statistic matrix, mostly for internal use.

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  NPC(rawStats, combFun = "Fisher", seed, p.values = FALSE,
    tails = NULL, subsets = NULL, weights = NULL,
    iteratedNPC = FALSE)

`rawStats`	3-ways `array` containing the test statistic computed on all pairwise comparisons (both directions) in all variables, with dimensions B+1 x p x K, where `B` is the number of permutations, `p` is the number of variables and `K` is the number of pairwise comparisons.
`combFun`	`character` string indicating the combining function to be used, can take as input p-values or the raw test statistic depending on the choice, can be one of `"Fisher"`, `"Liptak"`, `"minP"`, `"Tippett"`, `"maxT"`, `"sumT"` and `"direct"`; note that `"direct"` is equivalent to `"sumT"` and `"Tippett"` is equivalent to `"minP"`. `"Liptak"` use the normal quantile function. See references for details.
`seed`	`integer` seed for the `RNG` (random number generator), taken from the input for reproducibility purposes
`p.values`	`logical`, if `TRUE` means that the input matrix `rawStats` contains p-values rather than raw test statistics and so has to be treated differently, i.e. the first passage from test statistics to p-values is omitted (function `t2p`)
`tails`	`integer` vector of {+1,-1} containing the alternatives for response variables: `+1` means “the higher the better”, `-1` means “the lower the better” (direction of preference), if `NULL` (default) all variables are considered to be of the type “the higher the better'
`subsets`	`integer`, `character` or `list` where each element contains the subset of column indices that need to be treated separately, if `NULL` (default) all input variables are considered
`weights`	`integer`, `character` or `list` where each element contains the weights of the variables, one for each `subset`, if `NULL` (default) variables are treated equally i.e. all have the same weight
`iteratedNPC`	`logical`, if `TRUE` it performs the iterated combination procedure running function `iterNPC` and the choice of `comb.funct` becomes thus irrelevant; otherwise just perform the requested NPC.

It takes as input the 3-ways matrix containing the raw test statistics and perform the NPC with the possibility to add sets of weights for weighting variables differently, and/or to select subsets of variables to which NPC has to be applied separately. Note that weights and subsets are placed in the “...” argument of the SOUP function call hence they are not documented in the SOUP help.

an object of class PermSpace or a list containing PermSpace objects, in the case of multiple weights and/or subsets.

This function is mainly taken from the function npc in the package flip.

Federico Mattiello <federico.mattiello@gmail.com>

Pesarin, F. and Salmaso, L. (2010) Permutation Tests for Complex Data. Wiley: United Kingdom

Pesarin F. (2001) Multivariate Permutation Tests with Applications in Biostatistics. Wiley: New York.

t2p

SOUP documentation built on May 2, 2019, 8:18 a.m.