Statistical analysis of longitudinal studies. (17th October 2022)

• Record Type: Journal Article
• Authors: Laird, Nan M.
• Is Part Of: International statistical review. Volume 90(2022)Supplement 1
• Page Start: S2
• Page End: S16
• Publication Date: 2022-10-17
• Subjects: EM algorithm -- linear mixed model -- random effects -- studies of growth and change; Statistics -- Periodicals; Statistics -- Bibliography -- Periodicals; Statistics -- Bibliography; Statistics -- Periodicals; Statistique; Statistique -- Périodiques; Statistique -- Bibliographie -- Périodiques; Statistique -- Étude et enseignement -- Périodiques; Statistique -- Étude et enseignement -- Bibliographie -- Périodiques; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 519.2
• DOI: 10.1111/insr.12523
• Languages: English
• ISSNs: 0306-7734

Abstract

Summary: Longitudinal studies play a prominent role in research on growth, change and/or decline in individuals, and in characterising the environmental and social factors which influence change. The essential feature of a longitudinal study is taking repeated measures of an outcome on the same set of individuals at multiple timepoints, thereby allowing investigators to characterise within subject changes during the measurement period. This paper provides an overview of how the basic design features and analysis of longitudinal studies are related to other study designs, including longitudinal clinical trials as well as repeated measures studies. I summarise the use of the linear mixed model as described in Laird and Ware for the analysis of a broad class of designs and present some applications in health and medicine.