simasd_comm_df

<p>A dataset of partitions of nodes to communities from simulated group-level
networks with community structures. This dataset is complementary to the
simasd_covars dataset, which contains the demographic information related
to this dataset. For more information on how these group-level networks 
were simulated, please refer to the example script titled "beta_simulation_data.set.R".
The variables are as follows:</p>

datasets

Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).

Alexandria Jensen

CommKern

Network-Based Communities and Kernel Machine Methods

Peter DeWitt

Debashis Ghosh

simasd_comm_df function

<p>A dataframe with 80 rows and 49 columns, where rows correspond to
nodes within the simulated networks and columns correspond to the subject ID.</p>

simasd_comm_df: Simulated partitions of nodes to communities from HMS algorithm

Description

Usage

Arguments

Format