Description Usage Arguments Details Value Author(s) See Also Examples
View source: R/permute_group.R
brainGraph_permute
draws permutations from linear model residuals to
determine the significance of betweengroup differences of a global or
vertexwise graph measure. It is intended for structural covariance networks
(in which there is only one graph per group), but can be extended to other
types of data.
1 2 3 4 
densities 
Numeric vector of graph densities 
resids 
An object of class 
N 
Integer; the number of permutations (default: 5e3) 
perms 
Numeric matrix of permutations, if you would like to provide
your own (default: 
auc 
Logical indicating whether or not to calculate differences in the
areaunderthecurve of metrics (default: 
level 
A character string for the attribute "level" to calculate
differences (default: 
measure 
A character string specifying the vertexlevel metric to
calculate, only used if 
atlas 
Character string of the atlas name; required if

.function 
A custom function you can pass if 
If you would like to calculate differences in the areaunderthecurve (AUC)
across densities, then specify auc=TRUE
.
There are three possible "levels":
graph Calculate modularity (Louvain algorithm), clustering coefficient, characteristic path length, degree assortativity, global efficiency, lobe assortativity, and edge asymmetry.
vertex Choose one of: betweenness centrality, degree, nodal efficiency, knearest neighbor degree, transitivity, or vulnerability.
other Supply your own function. This is useful if you want to
calculate something that I haven't hardcoded. It must take as its own
arguments: g
(a list of lists of igraph
graph objects); and
densities
(numeric vector).
An object of class brainGraph_permute
with input arguments in
addition to:
DT 
A data table with permutation statistics 
obs.diff 
A data table of the observed group differences 
groups 
Group names 
Christopher G. Watson, [email protected]
Other Group analysis functions: IndividualContributions
,
NBS
, brainGraph_GLM
,
brainGraph_boot
,
brainGraph_mediate
, mtpc
Other Structural covariance network functions: IndividualContributions
,
brainGraph_boot
,
brainGraph_init
, corr.matrix
,
get.resid
,
plot.brainGraph_resids
,
plot_volumetric
1 2 3 4 5 6 7 8 9  ## Not run:
myResids < get.resid(lhrh, covars)
myPerms < shuffleSet(n=nrow(myResids$resids.all), nset=1e3)
out < brainGraph_permute(densities, m, perms=myPerms, atlas='dk')
out < brainGraph_permute(densities, m, perms=myPerms, level='vertex')
out < brainGraph_permute(densities, m, perms=myPerms,
level='other', .function=myFun)
## End(Not run)

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