An interactive website for analytical method comparison and bias estimation

Regulatory standards mandate laboratories to perform studies to ensure accuracy and reliability of their test results. Method comparison and bias estimation are important components of these studies. We developed an interactive website for evaluating the relative performance of two analytical method...

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Bibliographic Details
Published inClinical biochemistry Vol. 50; no. 18; pp. 1025 - 1029
Main Authors Bahar, Burak, Tuncel, Ayse F., Holmes, Earle W., Holmes, Daniel T.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.12.2017
Subjects
Bias
Chemistry Techniques, Analytical - methods
Clinical chemistry
Clinical Laboratory Services
Data Accuracy
Humans
Internet
Method comparison
Programming Languages
R programming
Regression Analysis
Reproducibility of Results
Shiny
Software
Website
Method comparison
Website
Clinical chemistry
Shiny
R programming
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Summary:Regulatory standards mandate laboratories to perform studies to ensure accuracy and reliability of their test results. Method comparison and bias estimation are important components of these studies. We developed an interactive website for evaluating the relative performance of two analytical methods using R programming language tools. The website can be accessed at https://bahar.shinyapps.io/method_compare/. The site has an easy-to-use interface that allows both copy-pasting and manual entry of data. It also allows selection of a regression model and creation of regression and difference plots. Available regression models include Ordinary Least Squares, Weighted-Ordinary Least Squares, Deming, Weighted-Deming, Passing-Bablok and Passing-Bablok for large datasets. The server processes the data and generates downloadable reports in PDF or HTML format. Our website provides clinical laboratories a practical way to assess the relative performance of two analytical methods. •We built a website (https://bahar.shinyapps.io/method_compare/) by R language for method comparison and bias estimation.•Available regression models: Ordinary Least Squares, Deming and Passing-Bablok•Available plots: scatter plot, coefficient plot and Bland-Altman plot•Generated reports can be download in PDF or HTML format.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0009-9120
1873-2933
DOI:10.1016/j.clinbiochem.2017.08.008