Pmat {permuco}

Create a set of permutations/signflips.

Description

Compute a permutation matrix used as argument in aovperm, lmperm, clusterlm functions. The first column represents the identity permutation. Generally not suited for the "huh_jhun" method, as the dimension of this matrix does not correspond to the number of observations and may vary for different factors.

Usage

Pmat(np = 5000, n, type = "permutation", counting = "random")

Arguments

np

A numeric value for the number of permutations. Default is 5000.

n

A numeric value for the number of observations.

type

A character string to specify the type of transformations: "permutation" and "signflip" are available. See details.

counting

A character string to specify the selection of the transformations. "all" and "random" are available. See details.

Details

couting can set to :
"random" : np random with replacement permutations/signflips among the n!/2^n permutations/signflips.
"all" : all n!/2^n possible permutations/signflips.

Value

A matrix n x np containing the permutations/signflips. First permutation is the identity.

See Also

Other pmat: Pmat_product(), as.Pmat()

Examples

## data
data("emergencycost")

## Create a set of 2000 permutations
set.seed(42)
pmat = Pmat(np = 2000, n = nrow(emergencycost))
sfmat = Pmat(np = 2000, n = nrow(emergencycost), type = "signflip")

## centrering the covariate to the mean
emergencycost$LOSc <- scale(emergencycost$LOS, scale = FALSE)

## ANCOVA
mod_cost_0 <- aovperm(cost ~ LOSc*sex*insurance, data = emergencycost, np = 2000)
mod_cost_1 <- aovperm(cost ~ LOSc*sex*insurance, data = emergencycost, P = pmat)
mod_cost_2 <- aovperm(cost ~ LOSc*sex*insurance, data = emergencycost, P = pmat)
mod_cost_3 <- aovperm(cost ~ LOSc*sex*insurance, data = emergencycost, P = sfmat)
mod_cost_4 <- aovperm(cost ~ LOSc*sex*insurance, data = emergencycost,type="signflip")

## Same p-values for both models 1 and 2 but different of model 0
mod_cost_0
mod_cost_1
mod_cost_2
mod_cost_3
mod_cost_4