TY - JOUR
T1 - Identifying subgroups
T2 - Part 2: Trajectories of change over time
AU - Lee, Christopher S.
AU - Faulkner, Kenneth M.
AU - Thompson, Jessica H.
N1 - Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by a grant from the National Institutes of Health/National Institute of Nursing Research (1R01NR013492 - Lee). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Nursing Research or the National Institutes of Health.
Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by a grant from the National Institutes of Health/National Institute of Nursing Research (1R01NR013492 - Lee). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Nursing Research or the National Institutes of Health.
Publisher Copyright:
© The European Society of Cardiology 2020.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - 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.
AB - 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.
KW - Latent growth mixture modeling
KW - latent class analysis
KW - longitudinal methods
KW - structural equation modeling
KW - subgroup analysis
KW - trajectories
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U2 - 10.1177/1474515120911330
DO - 10.1177/1474515120911330
M3 - Article
C2 - 32131616
AN - SCOPUS:85081628332
VL - 19
SP - 444
EP - 450
JO - European Journal of Cardiovascular Nursing
JF - European Journal of Cardiovascular Nursing
SN - 1474-5151
IS - 5
ER -