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Matematicheskaya Biologiya i Bioinformatika, 2020, Volume 15, Issue 2, Pages 416–428
DOI: https://doi.org/10.17537/2020.15.416
(Mi mbb439)
 

This article is cited in 1 scientific paper (total in 1 paper)

Information and Computer Technologies in Biology and Medicine

Assessing diagnostic accuracy of quantitative data in biomedical studies using descriptive statistics and standardized mean difference

A. A. Glazkova, D. A. Kulikovab, P. A. Glazkovaa

a Moscow Regional Research and Clinical Institute, Moscow, Russia
b Moscow Region State University, Moscow Region, Mytishchi, Russia
References:
Abstract: ROC analysis is the most used method for analyzing the diagnostic accuracy of quantitative data in biomedical research. ROC analysis generates a curve describing the frequencies of true positive and false positive results for different degrees of the analyzed variable. However, in many publications devoted to the application of quantitative diagnostic methods, this analysis is not carried out: researchers report only analysis of statistical significance for the groups difference. In meta-analyses, the estimated parameter is the effect size expressed through standardized mean difference. The article describes the approach, which allows performing ROC analysis using cumulative normal distribution functions for studied and controlling groups. The proposed approach can be used to evaluate the diagnostic accuracy of quantitative variables on the base of one of the sets of descriptive statistics (mean and standard deviation, or median and quartiles) or the value of standardized mean difference. Examples of application of the proposed approach on model data, on data from literature sources, as well as on the authors' own observations are given as an example of assessment of diagnostic accuracy of quantitative variables analyzed in the microcirculation studies in various diseases. The results presented in the article can be used by medical and biological specialists to assess the diagnostic accuracy of various quantitative variables without access to primary data.
Key words: standardized mean difference, diagnostic accuracy, ROC-analysis, statistics in medicine, normal distributions, simulation.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation МК-1786.2020.7
The reported study was funded by the grant of the President of the Russian Federation, grant number MK-1786.2020.7 (agreement No. 075-15-2020-354).
Received 19.10.2020, 02.12.2020, Published 17.12.2020
Document Type: Article
Language: Russian
Citation: A. A. Glazkov, D. A. Kulikov, P. A. Glazkova, “Assessing diagnostic accuracy of quantitative data in biomedical studies using descriptive statistics and standardized mean difference”, Mat. Biolog. Bioinform., 15:2 (2020), 416–428
Citation in format AMSBIB
\Bibitem{GlaKulGla20}
\by A.~A.~Glazkov, D.~A.~Kulikov, P.~A.~Glazkova
\paper Assessing diagnostic accuracy of quantitative data in biomedical studies using descriptive statistics and standardized mean difference
\jour Mat. Biolog. Bioinform.
\yr 2020
\vol 15
\issue 2
\pages 416--428
\mathnet{http://mi.mathnet.ru/mbb439}
\crossref{https://doi.org/10.17537/2020.15.416}
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  • https://www.mathnet.ru/eng/mbb/v15/i2/p416
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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    Full-text PDF :480
    References:19
     
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