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A PC program for computing McMahan's tracking indices from one-sample longitudinal data sets

I Y Guo1, T R Ten Have, C J Kowalski

  • 1Department of Public Health Sciences, Baylor College of Dentistry, Dallas, TX 75266-0677.

International Journal of Bio-Medical Computing
|May 1, 1994
PubMed
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This study introduces four tracking indices to measure consistent individual growth patterns over time. The research provides computational tools and compares these new indices against existing methods for assessing growth behavior.

Area of Science:

  • Biometrics
  • Longitudinal Data Analysis
  • Growth Modeling

Background:

  • Tracking describes consistent growth patterns where individuals maintain relative positions in a changing distribution over time.
  • Existing definitions of tracking focus on the regularity of individual growth trajectories within a population.

Purpose of the Study:

  • To introduce and describe four novel indices for quantifying tracking in longitudinal data.
  • To provide a computational tool for calculating these tracking indices.
  • To compare the proposed indices with alternative measures of tracking.

Main Methods:

  • Utilized four tracking indices developed by McMahan (1981).
  • Developed a program in GAUSS386i for index computation.
  • Applied indices to a longitudinal sample and compared results with alternative measures.

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Main Results:

  • The study presents four specific indices for measuring tracking.
  • A GAUSS386i program is provided for practical application of these indices.
  • McMahan's indices were compared to other tracking measures in an example.

Conclusions:

  • The proposed indices offer a quantitative approach to assessing growth tracking.
  • The provided computational tool facilitates the application of these biometrical measures.
  • This work contributes to the statistical analysis of longitudinal growth patterns.