mincAnova: Voxel-wise ANOVA Compute a sequential ANOVA at each voxel

In Mouse-Imaging-Centre/RMINC: Statistical Tools for Medical Imaging NetCDF (MINC) Files

Voxel-wise ANOVA Compute a sequential ANOVA at each voxel

Description

Voxel-wise ANOVA

Compute a sequential ANOVA at each voxel

Usage

mincAnova(
  formula,
  data = NULL,
  subset = NULL,
  mask = NULL,
  maskval = NULL,
  parallel = NULL,
  cleanup = TRUE,
  conf_file = getOption("RMINC_BATCH_CONF")
)

Arguments

formula	The anova formula. The left-hand term consists of the MINC filenames over which to compute the models at every voxel.
data	The dataframe which contains the model terms.
subset	Subset definition.
mask	Either a filename or a vector of values of the same length as the input files. ANOVA will only be computed inside the mask.
maskval	the value in the mask used to select unmasked voxels, defaults to any positive intensity from 1-99999999 internally expanded to .5 - 99999999.5. If a number is specified voxels with intensities within 0.5 of the chosen value are considered selected.
parallel	how many processors to run on (default=single processor). Specified as a two element vector, with the first element corresponding to the type of parallelization, and the second to the number of processors to use. For local running set the first element to "local" or "snowfall" for back-compatibility, anything else will be run with batchtools see pMincApply Leaving this argument NULL runs sequentially.
cleanup	Whether or not to remove parallelization files
conf_file	A batchtools configuration file defaulting to getOption("RMINC_BATCH_CONF")

Details

This function computes a sequential ANOVA over a set of files.

Value

Returns an array with the F-statistic for each model specified by formula with the following attributes:

• model design matrix

• filenames minc file names input

• dimensions dimensions of the statistics matrix

• dimnames names of the dimensions for the statistic matrix

• stat-type types of statistic used

• df degrees of freedom of each statistic

See Also

mincWriteVolume,mincFDR,mincMean, mincSd

Examples

## Not run:  
getRMINCTestData() 
# read the text file describing the dataset
gf <- read.csv("/tmp/rminctestdata/test_data_set.csv")
# run an ANOVA at each voxel
vs <- mincAnova(jacobians_fixed_2 ~ Sex, gf)

## End(Not run)

Mouse-Imaging-Centre/RMINC documentation built on Nov. 12, 2022, 1:50 p.m.