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Statistical analysis of longitudinal studies

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  • Nan M. Laird

Abstract

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.

Suggested Citation

  • Nan M. Laird, 2022. "Statistical analysis of longitudinal studies," International Statistical Review, International Statistical Institute, vol. 90(S1), pages 2-16, December.
    • Handle: RePEc:bla:istatr:v:90:y:2022:i:s1:p:s2-s16
    DOI: 10.1111/insr.12523
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    Cited by:

    1. Elena N. Naumova & Ryan B. Simpson & Bingjie Zhou & Meghan A. Hartwick, 2022. "Global seasonal and pandemic patterns in influenza: An application of longitudinal study designs," International Statistical Review, International Statistical Institute, vol. 90(S1), pages 82-95, December.

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