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Multilevel moderated mediation model with ordinal outcome.

Šárka Rusá1, Arnošt Komárek1, Emmanuel Lesaffre2

  • 1Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic.

Statistics in Medicine
|February 21, 2018
PubMed
Summary

This study introduces a flexible moderated mediation model for complex nursing data. The new Bayesian approach and software jointly handle clustered data, multiple mediators, and ordinal outcomes, advancing mediation analysis.

Keywords:
Bayesian multilevel modelinglatent variablesmoderated mediation modelordinal outcome

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Area of Science:

  • Statistics
  • Health Services Research
  • Nursing Research

Background:

  • Existing mediation models lack flexibility for complex data structures.
  • There is a need for integrated software handling multiple mediation generalizations.
  • Nursing research often involves clustered data, multiple mediators, and ordinal outcomes.

Purpose of the Study:

  • To propose a flexible moderated mediation model.
  • To jointly incorporate hierarchical data, multiple/correlated mediators, and ordinal outcomes.
  • To develop a Bayesian approach and software for these complex mediation analyses.

Main Methods:

  • Developed a flexible moderated mediation model.
  • Utilized a Bayesian approach for statistical analysis.
  • Created accompanying software to implement the model.

Main Results:

  • The proposed model accommodates hierarchical data structures.
  • The model handles multiple and correlated mediators effectively.
  • The approach is suitable for ordinal outcome variables.

Conclusions:

  • The developed Bayesian approach and software offer a unified solution for complex mediation.
  • This flexible model advances mediation analysis in nursing and other fields.
  • The methodology is applicable to real-world nursing research data.