anovagamVoxel function

Computes voxelwise analysis of variance (ANOVA) tables for a Generalized Additive Model.

This function computes analysis of variance tables for the fitted models after running a Generalized Additive Model (from mgcv::gam). The analysis will run in all voxels in the mask and will return the analysis of variance table for each voxel. Please check the mgcv::anova.gam documentation for further information about specific arguments used in anova.gam. Multi-model calls are disabled.

anovagamVoxel(image, mask, fourdOut = NULL, formula, subjData,
  dispersion = NULL, freq = FALSE, mc.preschedule = TRUE, ncores = 1,
  ...)

Arguments

• image: Input image of type 'nifti' or vector of path(s) to images. If multiple paths, the script will call mergeNifti() and merge across time.
• mask: Input mask of type 'nifti' or path to mask. Must be a binary mask
• fourdOut: To be passed to mergeNifti, This is the path and file name without the suffix to save the fourd file. Default (NULL) means script won't write out 4D image.
• formula: Must be a formula passed to gam()
• subjData: Dataframe containing all the covariates used for the analysis
• dispersion: To be passed to mgcv::anova.gam, Defaults to NULL. Dispersion Parameter, not normally used.
• freq: To be passed to mgcv::anova.gam, Defaults to FALSE. Frequentist or Bayesian approximations for p-values
• mc.preschedule: Argument to be passed to mclapply, whether or not to preschedule the jobs. More info in parallel::mclapply
• ncores: Number of cores to use
• ...: Additional arguments passed to gam()

Returns

Returns list of models fitted to each voxel over the masked images passed to function.

Examples

image <- oro.nifti::nifti(img = array(1:200, dim =c(2,2,2,25)))
mask <- oro.nifti::nifti(img = array(0:1, dim = c(2,2,2,1)))
set.seed(1)
covs <- data.frame(x = runif(25), y=runif(25))
fm1 <- "~ s(x) + y"
models <- anovagamVoxel(image=image, mask=mask,
              formula=fm1, subjData=covs, ncores = 1)