CVIA Journal

Announcing a new article publication for Cardiovascular Innovations and Applications journal. Cardiovascular disease develops through gradual accumulation of risk factors and progressive vascular damage. Longitudinal studies are well suited to determine when and how these changes occur, but they introduce several analytic challenges, including repeated measurements on the same individuals, irregular or sparse follow-up schedules, missing data, and non-linear trajectories.

The authors of this article conducted a narrative, application-focused review categorizing methods into five major classes: traditional or marginal models, mixed-effect models, joint models, trajectory and mixture models, and functional or machine-learning approaches. For each class, we provide intuitive descriptions, typical cardiovascular applications, and a balanced discussion of assumptions, strengths, limitations, and recommended sensitivity analyses.

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