++ 3dANOVA: AFNI version=AFNI_2011_12_21_1014 (Dec 16 2015) [64-bit] ++ Authored by: B. Douglas Ward This program performs a two-factor Analysis of Variance (ANOVA) on 3D datasets
Usage:
3dANOVA2
- -type\ k : type of ANOVA model to be used:
- k=1 fixed effects model (A and B fixed) k=2 random effects model (A and B random) k=3 mixed effects model (A fixed, B random)
-alevels a : a = number of levels of factor A
-blevels b : b = number of levels of factor B
- -dset\ 1 1 filename : data set for level 1 of factor A
and level 1 of factor B. . . . . .
- -dset i j filename : data set for level i of factor A
and level j of factor B. . . . . .
- -dset a b filename : data set for level a of factor A
- and level b of factor B
[-voxel num] : screen output for voxel # num
- [-diskspace\ ] : print out disk space required for
- program execution
- [-mask\ mset] : use sub-brick #0 of dataset ‘mset’
- to define which voxels to process
The following commands generate individual AFNI 2-sub-brick datasets:
- (In each case, output is written to the file with the specified
- prefix file name.)
[-ftr prefix] : F-statistic for treatment effect
[-fa prefix] : F-statistic for factor A effect
[-fb prefix] : F-statistic for factor B effect
[-fab prefix] : F-statistic for interaction
[-amean i prefix] : estimate mean of factor A level i
[-bmean j prefix] : estimate mean of factor B level j
- [-xmean\ i j prefix] : estimate mean of cell at level i of factor A,
- level j of factor B
[-adiff i j prefix] : difference between levels i and j of factor A
[-bdiff i j prefix] : difference between levels i and j of factor B
- [-xdiff\ i j k l prefix] : difference between cell mean at A=i,B=j
- and cell mean at A=k,B=l
[-acontr c1 ... ca prefix] : contrast in factor A levels
[-bcontr c1 ... cb prefix] : contrast in factor B levels
- [-xcontr c11 ... c1b c21 ... c2b ... ca1 ... cab prefix]
- : contrast in cell means
The following command generates one AFNI ‘bucket’ type dataset:
- [-bucket\ prefix] : create one AFNI ‘bucket’ dataset whose
- sub-bricks are obtained by concatenating the above output files; the output ‘bucket’ is written to file with prefix file name
Modified ANOVA computation options: (December, 2005)
- ** These options apply to model type 3, only.
- For details, see http://afni.nimh.nih.gov/sscc/gangc/ANOVA_Mod.html
- [-old_method\ ] : request to perform ANOVA using the previous
- functionality (requires -OK, also)
- [-OK\ ] : confirm you understand that contrasts that
- do not sum to zero have inflated t-stats, and contrasts that do sum to zero assume sphericity (to be used with -old_method)
[-assume_sph] : assume sphericity (zero-sum contrasts, only)
This allows use of the old_method for computing contrasts which sum to zero (this includes diffs, for instance). Any contrast that does not sum to zero is invalid, and cannot be used with this option (such as ameans).
Example of 3dANOVA2:
Example is based on a study with a 3 x 4 mixed factorial design:
- Factor 1 - DONUTS has 3 levels:
- chocolate, (2) glazed, (3) sugar
- Factor 2 - SUBJECTS, of which there are 4 in this analysis:
- fred, (2) ethel, (3) lucy, (4) ricky
- 3dANOVA2 -type 3 -alevels 3 -blevels 4
- -dset 1 1 fred_choc+tlrc -dset 2 1 fred_glaz+tlrc -dset 3 1 fred_sugr+tlrc -dset 1 2 ethel_choc+tlrc -dset 2 2 ethel_glaz+tlrc -dset 3 2 ethel_sugr+tlrc -dset 1 3 lucy_choc+tlrc -dset 2 3 lucy_glaz+tlrc -dset 3 3 lucy_sugr+tlrc -dset 1 3 ricky_choc+tlrc -dset 2 3 ricky_glaz+tlrc -dset 3 3 ricky_sugr+tlrc -amean 1 Chocolate -amean 2 Glazed -amean 3 Sugar -adiff 1 2 CvsG -adiff 2 3 GvsS -adiff 1 3 CvsS -acontr 1 1 -2 CGvsS -acontr -2 1 1 CvsGS -acontr 1 -2 1 CSvsG -fa Donuts -bucket ANOVA_results
The -bucket option will place all of the 3dANOVA2 results (i.e., main effect of DONUTS, means for each of the 3 levels of DONUTS, and contrasts between the 3 levels of DONUTS) into one big dataset with multiple sub-bricks called ANOVA_results+tlrc.
This program accepts datasets that are modified on input according to the following schemes:
‘r1+orig[3..5]’ {sub-brick selector} ‘r1+orig<100..200>’ {sub-range selector} ‘r1+orig[3..5]<100..200>’ {both selectors} ‘3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )’ {calculation}
For the gruesome details, see the output of ‘afni -help’.
The default output format is to store the results as scaled short (16-bit) integers. This truncantion might cause significant errors. If you receive warnings that look like this:
+ WARNING: TvsF[0] scale to shorts misfit = 8.09% – ** Beware
then you can force the results to be saved in float format by defining the environment variable AFNI_FLOATIZE to be YES before running the program. For convenience, you can do this on the command line, as in
3dANOVA -DAFNI_FLOATIZE=YES ... other options ...
++ Compile date = Dec 16 2015