Longitudinal analysis is concerned with studying the progression of the values of a variable over time for the members of a population. If time is defined as a categorical variable, longitudinal analysis is closely related to multivariate analysis, studying vectors of outcomes. When time is a continuous variable, longitudinal analysis studies the subjects’ curves (trajectories), and random coefficient models are well suited for this purpose. We can associate each time point with a separate variable, in the spirit of the original definition of the term variable. Then longitudinal analysis is the study of collections of variables; in most applications the variables are strongly associated. Features of this association are frequently the targets of inference.
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© 2008 Springer
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(2008). Longitudinal and Time-Series Analysis. In: Studying Human Populations. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-73251-0_11
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DOI: https://doi.org/10.1007/978-0-387-73251-0_11
Publisher Name: Springer, New York, NY
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