Session Information
09 SES 07 A, Modelling Longitudinal and Trend Data (part 1)
Symposium, Continued in 09 SES 08 A
Contribution
Numerous desiderata for future research in educational science require data from longitudinal studies. These data allow for the modelling of change in students characteristics (e.g. academic achievement). As the analysis of longitudinal data is much more sophisticated than the analysis of cross-sectional data scientists working with this kind of data have to be careful when choosing the appropriate model(s). With this paper we present an overview on this field of research and thereby give an introduction to the topic of this symposium “Modelling Longitudinal Data”. We will outline the central problems arising when modelling longitudinal data and name the most popular state-of-the-art methods for the analysis of change in academic achievement of students. Furthermore we will introduce the topics of the other five symposium papers.
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