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Some Models and Their Extensions for Longitudinal Analyses

In: Data Science and SDGs

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  • Tapio Nummi

    (Tampere University, Faculty of Information Technology and Communication Sciences)

Abstract

In this article, I present some of my statistical research in the field of longitudinal data analysis along with applications of these methods to real data sets. The aim is not to cover the whole field; rather, the perspective is based on my own personal preferences. The presented methods are mainly based on growth curve and mixture regression models and their extensions, where the focus is on continuous longitudinal data. In addition, an example of the analysis of extensive register data for categorical longitudinal data is presented. Applica-tions range from forestry and health sciences to social sciences.

Suggested Citation

  • Tapio Nummi, 2021. "Some Models and Their Extensions for Longitudinal Analyses," Springer Books, in: Bikas Kumar Sinha & Md. Nurul Haque Mollah (ed.), Data Science and SDGs, pages 15-30, Springer.
    • Handle: RePEc:spr:sprchp:978-981-16-1919-9_2
    DOI: 10.1007/978-981-16-1919-9_2
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