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Gastrointestinal Motility Monitor GIMM
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Network Mapping with GIMME.

Adriene M Beltz1, Kathleen M Gates2

  • 1a Department of Psychology , University of Michigan , Ann Arbor , MI , USA.

Multivariate Behavioral Research
|November 22, 2017
PubMed
Summary
This summary is machine-generated.

This tutorial simplifies network analysis using group iterative multiple model estimation (GIMME) for longitudinal data. Researchers can now easily create personalized networks to understand variable relationships and temporal dynamics.

Keywords:
Connectivityidiographic vs. nomothetic methodsintensive longitudinal datatime series analysisunified structural equation modeling

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Area of Science:

  • Network science
  • Quantitative psychology
  • Data analysis

Background:

  • Network science offers compelling insights but implementation can be challenging.
  • Automated network analysis methods are needed for complex data.

Purpose of the Study:

  • To provide a tutorial on implementing group iterative multiple model estimation (GIMME) for network analysis.
  • To facilitate the use of GIMME for researchers analyzing intensive longitudinal data.

Main Methods:

  • Conceptual and mathematical descriptions of GIMME.
  • Practical guidance on data acquisition, preprocessing, and program operation.
  • Step-by-step analysis of an empirical data set using the GIMME pipeline.

Main Results:

  • Demonstration of how GIMME creates person-specific networks.
  • Explanation of how to interpret network relations for prediction.
  • Overview of GIMME extensions for diverse research questions.

Conclusions:

  • Researchers will be equipped to analyze temporal dynamics in heterogeneous time series data using GIMME.
  • GIMME offers a powerful, automated approach to network analysis for individual differences.