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Julian Burger1, Adela-Maria Isvoranu2, Gabriela Lunansky2

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This summary is machine-generated.

This study introduces reporting standards for statistical network analyses in psychological research. These guidelines aim to improve transparency and reproducibility in documenting network models and results.

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Area of Science:

  • Psychology
  • Statistics
  • Data Science

Background:

  • Statistical network models are increasingly used for psychological data.
  • Existing tutorials focus on network estimation, not reporting standards.
  • Lack of reporting guidelines can lead to researcher degrees of freedom and questionable practices.

Purpose of the Study:

  • Introduce novel reporting standards for network analyses in cross-sectional psychological data.
  • Provide a tutorial and examples to guide researchers, reviewers, and editors.
  • Enhance transparency and reproducibility in the field of network analysis.

Main Methods:

  • Development of reporting standards for network analyses.
  • Inclusion of a tutorial and practical examples.
  • Focus on cross-sectional data.

Main Results:

  • A comprehensive set of reporting guidelines for network analyses is presented.
  • The guidelines address documentation of analyses and results.
  • Examples illustrate the application of the proposed standards.

Conclusions:

  • Standardized reporting is crucial for the advancement of network models in psychology.
  • These guidelines will benefit researchers, reviewers, and editors.
  • Improved reporting fosters transparency and reduces questionable research practices.