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Modeling the Functional Network for Spatial Navigation in the Human Brain

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Published on: October 13, 2023

Estimating psychological networks and their accuracy: A tutorial paper.

Sacha Epskamp¹, Denny Borsboom², Eiko I Fried²

¹Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands. sacha.epskamp@gmail.com.

Behavior Research Methods

|March 26, 2017

Summary

This summary is machine-generated.

This study introduces methods to assess the accuracy and stability of psychological networks, crucial for understanding complex behaviors. The R-package bootnet is provided to aid researchers in network analysis and interpretation.

Keywords:

Bootstrap Network psychometrics Psychological networks Replicability Tutorial

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Area of Science:

Psychology
Network Science
Computational Statistics

Background:

Psychological networks are increasingly used to model complex behaviors.
Limited research exists on the accuracy and stability of these network estimations.
Understanding sampling variation is crucial for reliable network interpretation.

Purpose of the Study:

To introduce methods for assessing the accuracy and stability of psychological networks.
To address the problem of accuracy under sampling variation in network analysis.
To present novel statistical methods and an accompanying R-package for network assessment.

Main Methods:

Review of current state-of-the-art network estimation techniques.
Application of bootstrap routines to assess network connections and centrality indices.
Introduction of the correlation stability coefficient and bootstrapped difference test.

Main Results:

Simulation studies demonstrate the performance of the novel statistical methods.
The R-package bootnet facilitates generalized network estimation and bootstrap methods.
Tutorial analysis showcases bootnet with a posttraumatic stress disorder dataset.

Conclusions:

Researchers can now better evaluate the accuracy and stability of psychological networks.
The bootnet package provides a practical tool for robust network analysis.
Accurate network inferences are essential for advancing psychological research.