Sample size estimation in diagnostic test studies of biomedical informatics

J Biomed Inform. 2014 Apr:48:193-204. doi: 10.1016/j.jbi.2014.02.013. Epub 2014 Feb 26.


Objectives: This review provided a conceptual framework of sample size calculations in the studies of diagnostic test accuracy in various conditions and test outcomes.

Methods: The formulae of sample size calculations for estimation of adequate sensitivity/specificity, likelihood ratio and AUC as an overall index of accuracy and also for testing in single modality and comparing two diagnostic tasks have been presented for desired confidence interval.

Results: The required sample sizes were calculated and tabulated with different levels of accuracies and marginal errors with 95% confidence level for estimating and for various effect sizes with 80% power for purpose of testing as well. The results show how sample size is varied with accuracy index and effect size of interest.

Conclusion: This would help the clinicians when designing diagnostic test studies that an adequate sample size is chosen based on statistical principles in order to guarantee the reliability of study.

Keywords: Area under the curve; Diagnostic studies; ROC analysis; Sample size; Sensitivity; Specificity.

MeSH terms

  • Algorithms
  • Confidence Intervals
  • Diagnostic Tests, Routine / methods*
  • Humans
  • Likelihood Functions
  • Medical Informatics / methods*
  • Models, Statistical
  • ROC Curve
  • Reproducibility of Results
  • Research Design
  • Sample Size
  • Sensitivity and Specificity