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Related Experiment Videos

How Significant Are "High" Correlations Between EQ-5D Value Sets?

Franz Ombler1, Michael Albert1, Paul Hansen2

  • 1Department of Computer Science, University of Otago, Dunedin, New Zealand.

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|June 8, 2018
PubMed
Summary
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High correlations in EQ-5D value sets do not necessarily mean similar health preferences. Our study shows these high correlations are often artifacts of the data structure, not true preference agreement.

Area of Science:

  • Health Economics
  • Psychometrics
  • Biostatistics

Background:

  • Quality-adjusted life years (QALYs) are crucial for cost-utility analysis.
  • QALY calculations rely on value sets reflecting health-related quality of life (HRQoL) preferences.
  • The EQ-5D is the most widely used system for generating HRQoL value sets.

Purpose of the Study:

  • To investigate whether high correlation coefficients between EQ-5D value sets indicate genuine similarity in HRQoL preferences.
  • To determine if conventional interpretations of high correlations are statistically sound.
  • To provide a method for assessing the significance of correlation coefficients in EQ-5D value sets.

Main Methods:

  • Simulated EQ-5D value sets using random data to assess correlation coefficients.
Keywords:
EQ-5Dcorrelationcritical valuehealth-related quality of lifestatistical significance

Related Experiment Videos

  • Calculated Pearson's r for EQ-5D-3L and EQ-5D-5L value sets derived from random data.
  • Determined significance levels for correlation coefficients based on simulation results.

    • Main Results:

    • High correlation coefficients (e.g., median r = 0.783 for EQ-5D-3L, 0.850 for EQ-5D-5L) were observed even with random data, indicating they are artifacts of inherent value set rankings.
    • Many conventionally interpreted high correlations were found to be not statistically significant.
    • Some high correlations were spurious, not reflecting meaningful associations in HRQoL preferences.

    Conclusions:

    • High correlation coefficients between EQ-5D value sets should not be automatically interpreted as evidence of similar HRQoL preferences.
    • The inherent structure of EQ-5D value sets can create spurious correlations.
    • Researchers should use simulation-based significance testing to avoid misinterpreting correlations in EQ-5D value sets.