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Related Experiment Videos

Implementation of Rao's one-sample polynomial growth curve model using SAS.

E D Schneiderman, C J Kowalski

    American Journal of Physical Anthropology
    |August 1, 1985
    PubMed
    Summary

    This study implements Rao's polynomial growth curve model in SAS for longitudinal data analysis. The method effectively analyzes correlated data, providing accurate confidence bands and parameter intervals for growth curves.

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    Area of Science:

    • Biostatistics
    • Longitudinal Data Analysis
    • Statistical Modeling

    Background:

    • Traditional analysis of variance and regression models assume independent observations, which is often violated in longitudinal studies.
    • The use of least-squares methods on serially correlated data can lead to frequent rejection of the null hypothesis.
    • Existing appropriate models for longitudinal data analysis have been limited by complex matrix manipulations.

    Purpose of the Study:

    • To implement Rao's one-sample polynomial growth curve model using SAS for analyzing longitudinal data.
    • To provide a user-friendly method for testing goodness-of-fit and calculating confidence bands for polynomial growth curves.
    • To compute confidence intervals for the parameters of fitted growth curve models.

    Main Methods:

    Related Experiment Videos

    • Implementation of Rao's (1959) polynomial growth curve model within the SAS programming environment.
    • Utilizing SAS's matrix language capabilities for efficient computation.
    • Testing goodness-of-fit and calculating confidence bands for polynomial growth curves at equally spaced time points.

    Main Results:

    • The study successfully implemented and illustrated Rao's model using SAS.
    • Examples with mandibular ramus height data in rhesus monkeys demonstrated adequate fitting with quadratic and linear equations.
    • The analysis highlighted the widening of confidence bands when over-parameterized polynomial equations are used.

    Conclusions:

    • Rao's polynomial growth curve model, implemented in SAS, offers an accessible approach to analyzing longitudinal data with correlated observations.
    • The method provides reliable goodness-of-fit testing and confidence interval calculations for growth curve parameters.
    • Accurate model selection is crucial to avoid misleading results due to overly complex polynomial fits.