Identifying subgroups: Part 2: Trajectories of change over time

Christopher S. Lee; Kenneth M. Faulkner; Jessica H. Thompson

doi:10.1177/1474515120911330

Identifying subgroups: Part 2: Trajectories of change over time

Christopher S. Lee
, Kenneth M. Faulkner
, Jessica H. Thompson

Office of the Dean of Nursing

Stony Brook University

Boston College

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

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
Pages (from-to)	444-450
Number of pages	7
Journal	European Journal of Cardiovascular Nursing
Volume	19
Issue number	5
DOIs	https://doi.org/10.1177/1474515120911330
State	Published - Jun 1 2020

Keywords

Latent growth mixture modeling
latent class analysis
longitudinal methods
structural equation modeling
subgroup analysis
trajectories

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10.1177/1474515120911330

Cite this

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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.",

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KW - longitudinal methods

KW - structural equation modeling

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Identifying subgroups: Part 2: Trajectories of change over time

Abstract

Keywords

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