Sample size calculations for model validation in linear regression analysis

Show Li Jan, Gwowen Shieh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Background: Linear regression analysis is a widely used statistical technique in practical applications. For planning and appraising validation studies of simple linear regression, an approximate sample size formula has been proposed for the joint test of intercept and slope coefficients. Methods: The purpose of this article is to reveal the potential drawback of the existing approximation and to provide an alternative and exact solution of power and sample size calculations for model validation in linear regression analysis. Results: A fetal weight example is included to illustrate the underlying discrepancy between the exact and approximate methods. Moreover, extensive numerical assessments were conducted to examine the relative performance of the two distinct procedures. Conclusions: The results show that the exact approach has a distinct advantage over the current method with greater accuracy and high robustness.

Original languageEnglish
Article number54
JournalBMC Medical Research Methodology
Issue number1
StatePublished - 12 Mar 2019


  • Linear regression
  • Model validation
  • Power
  • Sample size
  • Stochastic predictor

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