Longitudinal and Time-Series Analysis

Part of the Springer Texts in Statistics book series (STS)

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.


Mixture Model House Price Variance Matrix Markov Property Multivariate Normal Distribution 
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© Springer 2008

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