Identifying subgroups: Part 2: Trajectories of change over time
Christopher S. Lee, Kenneth M. Faulkner, Jessica Harman Thompson
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.
Topics & Concepts
MedicineAppealKey (lock)Latent growth modelingEconometricsLatent variableData scienceArtificial intelligenceComputer scienceMachine learningMathematicsLawComputer securityPolitical scienceStatistical Methods in Epidemiology