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Multiphasic growth curve analysis.

W.J. Koops

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Abstract

Application of a multiphasic growth curve is demonstrated with 4 data sets, adopted from literature. The growth curve used is a summation of n logistic growth functions. Human height growth curves of this type are known as "double logistic" (n = 2) and "triple logistic" (n = 3) growth curves (Bock and Thissen, 1976). In the literature there is also some evidence for the existence of growth phases in weight growth curves of animals. The fit of the multiphasic growth curve, applied to pika, mice and rabbit weights, was superior to the monophasic model in terms of residual variances and absence of autocorrelation of residuals.

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What this paper is about

Application of a multiphasic growth curve is demonstrated with 4 data sets, adopted from literature. The growth curve used is a summation of n logistic growth functions. Human height growth curves of this type are known as "double logistic" (n = 2) and "triple logistic" (n = 3) growth curves (Bock and Thissen, 1976). In the literature there is also some evidence for the existence of growth phases in weight growth curves of animals. The fit of the multiphasic growth curve, applied to pika, mice and rabbit weights, was superior to the monophasic model in terms of residual variances and absence of autocorrelation of residuals.

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Available abstract

Application of a multiphasic growth curve is demonstrated with 4 data sets, adopted from literature. The growth curve used is a summation of n logistic growth functions. Human height growth curves of this type are known as "double logistic" (n = 2) and "triple logistic" (n = 3) growth curves (Bock and Thissen, 1976). In the literature there is also some evidence for the existence of growth phases in weight growth curves of animals. The fit of the multiphasic growth curve, applied to pika, mice and rabbit weights, was superior to the monophasic model in terms of residual variances and absence of autocorrelation of residuals.

Key concepts: Growth curve (statistics), Logistic function, Autocorrelation, Mathematics, Logistic regression, Statistics, Residual, Curve fitting

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