parMap: Create parametric maps

In neuroconductor/voxel: Mass-Univariate Voxelwise Analysis of Medical Imaging Data

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

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

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.