brainGraph (version 3.1.1)

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, [email protected]

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')
}