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Related Experiment Videos

A two-step method for understanding and fitting growth curve models.

E J Stanek1

  • 1Division of Public Health, University of Massachusetts, Amherst 01003.

Statistics in Medicine
|July 1, 1990
PubMed
Summary
This summary is machine-generated.

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Growth curve analysis, often overlooked, can be simplified using variable transformation and weighted least squares (WLS). This approach makes complex models accessible with standard software, extending univariate repeated measures analysis.

Area of Science:

  • Multivariate Statistics
  • Longitudinal Data Analysis

Background:

  • Growth curve analysis using the Potthoff-Roy model is underutilized in repeated measures designs.
  • Lack of familiarity and accessible computational tools contribute to its limited application.

Purpose of the Study:

  • To present a simplified methodology for fitting growth curve models.
  • To demonstrate growth curve analysis as a natural extension of univariate repeated measures models.

Main Methods:

  • Utilizing variable transformation and weighted least squares (WLS) to fit growth models.
  • Employing a two-step methodology for model fitting.

Main Results:

  • Growth curve models can be fitted using readily available software.

Related Experiment Videos

  • The proposed method extends univariate repeated measures analysis and allows for more general growth models.

    • Conclusions:

    • Growth curve analysis can be effectively performed using accessible statistical techniques.
    • This approach facilitates the characterization of response profiles in longitudinal data.