vlmParam function

Run a Linear Model on all voxels of a NIfTI image within a mask and and return parametric coefficients tables

This function is able to run a Linear Model using the stats package. The analysis will run in all voxels in in the mask and will and will return parametric coefficients at each voxel.

vlmParam(image, mask, fourdOut = NULL, formula, 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 all 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 lm()
• 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
• ...: Additional arguments passed to lm()

Returns

Return list of parametric and spline coefficients (include standard errors and p-values) fitted to each voxel over the masked images passed to function.

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)