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Identifying subgroups: Part 2: Trajectories of change over time
Christopher S Lee1, Kenneth M Faulkner1, Jessica H Thompson1
1Boston College William F. Connell School of Nursing, USA.
European Journal of Cardiovascular Nursing
|March 6, 2020
Summary
Identifying multiple change trajectories is crucial in health research. Latent growth mixture modeling (LGMM) helps analyze distinct developmental paths for key health outcomes.
Area of Science:
- Health Research
- Nursing Research
- Biostatistics
Background:
- Understanding changes in health outcomes over time is vital.
- Identifying distinct patterns of change can inform interventions.
- Existing methods may not fully capture diverse trajectories.
Purpose of the Study:
- To introduce latent growth mixture modeling (LGMM) as a powerful analytic strategy.
- To demonstrate the application of LGMM with a worked example.
- To encourage the use of LGMM in health and nursing research.
Main Methods:
- Latent growth mixture modeling (LGMM) was employed.
- A data-centered analytic approach was utilized.
- A worked example illustrated the LGMM process.
Main Results:
- LGMM effectively identifies multiple distinct trajectories of change.
- The worked example highlights the practical application and benefits of LGMM.
- Researchers can gain deeper insights into outcome variability over time.
Conclusions:
- Latent growth mixture modeling is a valuable tool for analyzing change over time in health research.
- LGMM facilitates the study of diverse developmental pathways.
- This method enhances the understanding of key measures and outcomes in nursing and related fields.
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