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Regression-based reference limits: determination of sufficient sample size

A Virtanen1, V Kairisto, E Uusipaikka

  • 1Central Laboratory, University Central Hospital of Turku/Mircit (Medical Informatics Research Centre in Turku), Finland. arja.virtanen@utu.fi

Clinical Chemistry
|November 4, 1998
PubMed
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Determining appropriate sample sizes for regression-based reference limits is crucial. This study suggests a minimum sample size of approximately 70 for reliable covariate-dependent reference limits and confidence intervals.

Area of Science:

  • Clinical Chemistry
  • Biostatistics
  • Medical Laboratory Science

Background:

  • Regression analysis is standard for covariate-dependent reference limits.
  • No established guidelines exist for sample size in regression-based reference limit calculations.

Purpose of the Study:

  • To determine the minimum sample size required for accurate regression-based reference limits.
  • To evaluate the impact of sample size on the reliability of age-dependent reference intervals.

Main Methods:

  • Monte Carlo simulation using 5000 subsamples (10-220 observations) from a reference group of 374 hemoglobin values.
  • Regression analysis to estimate age-dependent 95% reference intervals for hemoglobin and erythrocyte counts.
  • Evaluation of root mean square error, parameter estimators, and width of reference intervals across varying sample sizes.

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Main Results:

  • Differences in root mean square error and reference interval width decreased with increasing sample size.
  • Parameter estimators and reference interval widths changed negligibly for sample sizes >= 60.
  • Standard deviations and coefficients of variation stabilized after a sample size of 30.

Conclusions:

  • A minimum sample size of approximately 70 is proposed for reliable regression-based reference limits.
  • Pre-analysis checks include verifying regression assumptions and covariate value distribution.
  • Accurate reference limits require careful consideration of sample size and regression model assumptions.