Abstract
One special type of series measured in time concerns changes related to growth. Measurements are made repeatedly on one or more individuals. One goal of such studies is often to predict future growth. Naturally, for a given individual, the observations usually will not be independent, but will be correlated. If several individuals are concerned, the interrelation may vary among the individuals. However, we shall ignore this problem, as has often been done with growth curves, until after we have looked at classical time series analysis in the next chapter. Here, we shall treat several examples of the simple case of one series of repeated measurements (i.e. on one individual) related to growth, leaving the case of measurements on several individuals to Chapter 8, when we shall be able to handle the correlation.
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© 1992 Springer-Verlag Berlin Heidelberg
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Lindsey, J.K. (1992). Growth Curves. In: The Analysis of Stochastic Processes using GLIM. Lecture Notes in Statistics, vol 72. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2888-2_5
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DOI: https://doi.org/10.1007/978-1-4612-2888-2_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-97761-4
Online ISBN: 978-1-4612-2888-2
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