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Multiphasic growth curve analysis.

W J Koops

    Growth
    |January 1, 1986
    PubMed
    Summary
    This summary is machine-generated.

    This study shows multiphasic growth curves, which sum logistic functions, better model animal weight gain than single models. This multiphasic approach improves accuracy for pika, mice, and rabbit weight data.

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    Area of Science:

    • Quantitative Biology
    • Biomathematics
    • Animal Science

    Background:

    • Growth curves are essential for understanding biological development.
    • Existing monophasic models may not capture complex growth patterns.
    • Multiphasic growth curves, like double or triple logistic models, have been proposed for human height and animal weight.

    Purpose of the Study:

    • To demonstrate the application of a multiphasic growth curve model.
    • To compare the fit of multiphasic versus monophasic models for animal weight data.
    • To evaluate the effectiveness of summing logistic functions for modeling growth.

    Main Methods:

    • Utilized a multiphasic growth curve model, defined as a summation of 'n' logistic growth functions.
    • Applied the model to four datasets from existing literature.

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  • Included weight data for pika, mice, and rabbits.
  • Compared model fit against a monophasic growth model.

    • Main Results:

    • The multiphasic growth curve model demonstrated superior fit compared to the monophasic model.
    • Improvements were observed in terms of reduced residual variances.
    • The multiphasic model showed an absence of autocorrelation in residuals, indicating a better fit.

    Conclusions:

    • Multiphasic growth curves provide a more accurate representation of animal weight dynamics than monophasic models.
    • The summation of logistic functions effectively captures complex growth phases.
    • This modeling approach offers enhanced analytical capabilities for biological growth studies.