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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
Summary
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.
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.
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