Time in Latent Growth Curve Models

Matt L. Miller () and Paolo Ghisletta ()
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Matt L. Miller: Arizona State University, REACH Institute
Paolo Ghisletta: University of Geneva, Faculty of Psychology and Educational Sciences

Chapter Chapter 2 in Dependent Data in Social Sciences Research, 2024, pp 43-63 from Springer

Abstract: Abstract Longitudinal research methods have brought the idea of change over time into social science research, but time itself is often paid little attention in the construction of analytical models. In this chapter, we look at how longitudinal data are analyzed in latent growth curve models. We focus on the real-world problem of sampling-time variation, when individuals do not have exactly equal intervals between measurements, its consequences, and how to handle it.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-56318-8_2

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DOI: 10.1007/978-3-031-56318-8_2

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