title: Multiple method comparison: statistical model using percentage similarity.
abstract: BACKGROUND
  Method comparison typically determines how well two methods agree. This is usually performed using the difference plot model, which measures absolute differences between two methods. This is often not applicable to data with wide ranges of absolute values. An alternative model is introduced that simplifies comparisons specifically for multiple methods compared to a gold standard.
  
  
  METHODS
  The average between a new method and the gold standard is represented as a percentage of the gold standard. This is interpreted as a percentage similarity value and accommodates wide ranges of data. The representation of the percentage similarity values in a histogram format highlights the accuracy and precision of several compared methods to a gold standard. The calculation of a coefficient of variation further defines agreement between methods.
  
  
  RESULTS
  Percentage similarity histograms of several new methods can be compared to a gold standard simultaneously, and the comparison easily visualized through use of a single 100% similarity reference line drawn common to all plots.
  
  
  CONCLUSIONS
  This simple method of comparison would be particularly useful for multiple method comparison and is especially applicable for centers collating for external quality assessment or assurance programs to demonstrate differences in results between laboratories.
authors.affiliation: Department of Molecular Medicine and Hematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. lesleys@mighty.co.za
authors.forename: Lesley E
authors.initials: LE
authors.lastname: Scott
authors.forename: Jacky S
authors.initials: JS
authors.lastname: Galpin
authors.forename: Deborah K
authors.initials: DK
authors.lastname: Glencross
mesh_terms: D001699:Biometry / Q000379:methods*; D018791:CD4 Lymphocyte Count / Q000379:methods* / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016008:Statistical Distributions