Abstract
Methods to identify multiple trajectories of change over time are of great interest in nursing and in related health research. Latent growth mixture modeling is a data-centered analytic strategy that allows us to study questions about distinct trajectories of change in key measures or outcomes of interest. In this article, a worked example of latent growth mixture modeling is presented to help expose researchers to the use and appeal of this analytic strategy.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 444-450 |
| Number of pages | 7 |
| Journal | European Journal of Cardiovascular Nursing |
| Volume | 19 |
| Issue number | 5 |
| DOIs | |
| State | Published - Jun 1 2020 |
Keywords
- Latent growth mixture modeling
- latent class analysis
- longitudinal methods
- structural equation modeling
- subgroup analysis
- trajectories
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine
- Medical–Surgical
- Advanced and Specialized Nursing
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Lee, C. S., Faulkner, K. M., & Thompson, J. H. (2020). Identifying subgroups: Part 2: Trajectories of change over time. European Journal of Cardiovascular Nursing, 19(5), 444-450. https://doi.org/10.1177/1474515120911330