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Related Experiment Videos

PRESS-related statistics: regression tools for cross-validation and case diagnostics

D B Holiday1, J E Ballard, B C McKeown

  • 1Department of Epidemiology/Biomathematics, University of Texas Health Center at Tyler 75710, USA.

Medicine and Science in Sports and Exercise
|April 1, 1995
PubMed
Summary
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Data-splitting for regression validation has drawbacks. The PRESS statistic offers an alternative, providing unbiased performance estimates without splitting data, especially useful for smaller datasets in health science research.

Area of Science:

  • Health Sciences
  • Biostatistics
  • Regression Analysis

Background:

  • Data-splitting is a common regression validation method in health sciences.
  • This technique uses a fitting sample for model development and a validation sample for performance estimation.
  • While it corrects for upward bias, data-splitting has practical limitations.

Purpose of the Study:

  • To contrast data-splitting with the PRESS statistic for regression equation validation.
  • To highlight the advantages of the PRESS statistic, particularly for smaller datasets.
  • To recommend reporting methods for these validation statistics.

Main Methods:

  • The study simulated data for predicting body density from anthropometric measurements.
  • It compared the traditional data-splitting method with the PRESS statistic.

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  • A dataset of 117 women was used for the simulation and comparison.

    • Main Results:

    • Data-splitting presents challenges including sample matching difficulties and reduced equation stability.
    • The PRESS statistic provides unbiased estimates of R2 and SEE without data splitting.
    • The PRESS method also offers valuable case diagnostics and is readily available in statistical software.

    Conclusions:

    • The PRESS statistic is a superior alternative to data-splitting for validating regression equations.
    • It is particularly advantageous for smaller datasets common in health science research.
    • Wider adoption of the PRESS statistic is recommended for robust regression model validation.