brainGraph (version 3.1.0)

IndividualContributions: Approaches to estimate individual network contribution

Description

loo calculates the individual contribution to group network data for each subject in each group using a “leave-one-out” approach. The residuals of a single subject are excluded, and a correlation matrix is created. This is compared to the original correlation matrix using the Mantel test.

aop calculates the individual contribution using an “add-one-patient” approach. The residuals of a single patient are added to those of a control group, and a correlation matrix is created. This is repeated for all individual patients and each patient group.

The summary method prints the group/region-wise means and standard deviations.

The plot method is only valid for regional contribution estimates, and plots the average regional contribution for each vertex/region.

Usage

loo(resids, corrs, level = c("global", "regional"))
aop(resids, corrs, level = c("global", "regional"), control.value = 1L)
# S3 method for IC
summary(object, region = NULL, digits = max(3L,
  getOption("digits") - 2L), ...)
# S3 method for IC
plot(x, plot.type = c("mean", "smooth", "boxplot"),
  region = NULL, ids = TRUE, ...)

Value

A data.table with columns for

Study.ID

Subject identifier

Group

Group membership

region

If level='regional'

IC,RC

The value of the individual/regional contributions

Arguments

resids

An object of class brainGraph_resids (the output from get.resid)

corrs

List of lists of correlation matrices (as output by corr.matrix).

level

Character string; the level at which you want to calculate contributions (either global or regional)

control.value

Integer or character string specifying the control group (default: 1L)

object, x

A IC object

region

Character vector specifying which regions' IC's to print. Only relevant if method='Leave one out'

digits

Integer specifying the number of digits to display for P-values

...

Unused

plot.type

Character string indicating the type of plot; the default is to plot the mean (along with standard errors)

ids

Logical indicating whether to plot Study ID's for outliers. Otherwise plots the integer index

Author

Christopher G. Watson,

References

Saggar, M. and Hosseini, S.M.H. and Buno, J.L. and Quintin, E. and Raman, M.M. and Kesler, S.R. and Reiss, A.L. (2015) Estimating individual contributions from group-based structural correlations networks. NeuroImage, 120, 274--284. tools:::Rd_expr_doi("10.1016/j.neuroimage.2015.07.006")

See Also

Other Structural covariance network functions: Bootstrapping, Residuals, brainGraph_permute, corr.matrix, import_scn, plot_volumetric

Examples

if (FALSE) {
IC <- loo(resids.all, corrs)
RC <- loo(resids.all, corrs, level='regional')
}
if (FALSE) {
IC <- aop(resids.all, corrs)
RC <- aop(resids.all, corrs, level='regional')
}