gammCluster function

Run a Generalized Additive Mixed Effects Model on the mean intensity over a region of interest

Run a Generalized Additive Mixed Effects Model on the mean intensity over a region of interest

This function is able to run a Generalized Additive Mixed Effects Model (GAMM) using the gamm4() function. All clusters or Regions of Interest must be labeled with integers in the mask passed as an argument.

gammCluster(image, mask, fourdOut = NULL, formula, randomFormula, subjData,
  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. All clusters must be labeled with integers in the mask passed as an argument
  • 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 gamm4()
  • randomFormula: Random effects formula passed to gamm4()
  • subjData: Dataframe containing all the covariates used for the analysis
  • 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 for the analysis
  • ...: Additional arguments passed to gamm4()

Returns

Returns list of models fitted to the mean voxel intensity a region or interest.

Examples

image <- oro.nifti::nifti(img = array(1:1600, dim =c(4,4,4,25)))
mask <- oro.nifti::nifti(img = array(c(rep(0,14),1,2), dim = c(4,4,4,1)))
set.seed(1)
covs <- data.frame(x = runif(25), id = rep(1:5,5))
fm1 <- "~ s(x)"
randomFormula <- "~(1|id)"
models <- gammCluster(image, mask, formula = fm1, 
                              randomFormula = randomFormula, subjData = covs, ncores = 1, REML=TRUE)
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