Title: Network Analysis with the R Package easybgm

Author: Karoline Huth

Abstract:
Network psychometrics is a recent approach to studying psychological
constructs as interconnected variables. Rather than treating variables as
independent entities, network analysis or graphical modeling views them as
nodes in a system that interact with each other; their interactions yield
partial associations. Recently, researchers have emphasized the use of
Bayesian methods in graphical modeling to accurately quantify uncertainty in
the model and its parameters. Several R packages have been developed that
implement different Bayesian estimation approaches for graphical modeling in
R. However, they all require different inputs and produce different outputs,
making them difficult to use for applied researchers. In this talk, we will
present a user-friendly R package called easybgm that combines the powerful
analysis tools into a cohesive package for applied researchers. The package
allows researchers to fit any type of cross-sectional data, extract results,
and visualize results such as network plots, edge evidence plots, and
structure uncertainty plots. We introduce the package and demonstrate its use
with an example on women and mathematics.