Measurements of Accuracy in Biostatistics

Haiying / HY Wang, Jyotsna Talreja Wassan, Huiru Zheng

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)
85 Downloads (Pure)


Due to the nature of biological and medical data, biostatistics has been playing an increasing role in a wide range of applications in biology and medicine. The aim of this article is to provide insights on some basic concepts and measurement procedures used in biostatistics. The amphasis has been placed on the application of biostatistics in the realm of classification aiming to design a good prediction model. Various statistical metrics and significance tests used to evaluate the performance of a predictor have been discussed. It has been highlighted that the interpretation of the values of these metrics should be cautious when applied to biological domain especially when dealing with highliy imbalanced datasets.
Original languageEnglish
Title of host publicationEncyclopedia of Bioinformatics and Computational Biology
EditorsShoba Ranganathan, Michael Gribskov, Kenta Nakai, Christian Schönbach
Number of pages6
ISBN (Electronic)9780128114148
ISBN (Print)9780128114322
Publication statusPublished (in print/issue) - 6 Sept 2018


  • Accuracy
  • Area under the ROC curve (AUC)ClassificationReceiver operating characteristic (ROC) curve
  • Classification
  • Receiver operating characteristic (ROC) curve
  • Test of Significance


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