parMap: Create parametric maps

Description Usage Arguments Value Examples

View source: R/parMap.R

Description

This function create parametric maps according from model parametric tables or analysis of variance tables. The function will return a p-map, t-map, signed z-map, p-adjusted-map for parametric terms and p-map, z-map, p-adjusted-map for smooth terms. Additionally the function will return a p-map, F-map, p-to-z-map, and p-adjusted-map if the input is ANOVA. You can select which type of p-value correction you want done on the map. The z-maps are signed just like FSL.

Usage

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parMap(parameters, mask, method = "none", outDir = NULL)

Arguments

parameters

list of parametric and smooth table coefficients or ANOVA (like the output from vlmParam, vgamParam, anovalmVoxel)

mask

Input mask of type 'nifti' or path to one. Must be a binary mask or a character. Must match the mask passed to one of vlmParam, vgamParam, vgamm4Param, vlmerParam

method

which method of correction for multiple comparisons (default is none)

outDir

Path to the folder where to output parametric maps (Default is Null, only change if you want to write maps out)

Value

Return parametric maps of the fitted models

Examples

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image <- oro.nifti::nifti(img = array(1:1600, dim =c(4,4,4,25)))
mask <- oro.nifti::nifti(img = array(0:1, dim = c(4,4,4,1)))
set.seed(1)
covs <- data.frame(x = runif(25), y = runif(25))
fm1 <- "~ x + y"
models <- vlmParam(image=image, mask=mask, 
              formula=fm1, subjData=covs, ncores = 1)
Maps <- parMap(models, mask, method="fdr")

neuroconductor/voxel documentation built on May 20, 2021, 9:39 p.m.