American Journal of Biomedical and Life Sciences

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Estimating False Rates-Based Relative Risk as Measure of Association in Diagnostic Screening Test

Received: 21 October 2013    Accepted:     Published: 30 November 2013
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Abstract

This paper proposes false-rates-based relative risk-type measure of the strength of association between state of nature or condition in a population and test results in diagnostic screening tests. The adopted method provides an estimate for the proposed relative risk that depends only on the estimated sensitivity and specificity of the test in the event that the prevalence rate is not known. The proposed method unlike the traditional odds ratio provides estimates of not only the proposed false rates based relative risk-type measure of association, but also alternative sample estimates of its associated standard deviation and test statistic for significance that intrinsically and structurally partials out, that is, does not include in its formulation the number of subjects in the sample known or believed to actually have the condition in nature but test negative or actually do not have the condition in nature but test positive to the condition in the screening test. The proposed method given that the prevalence rate of the condition in the population is known, provides sample estimates of the false positive rate, false negative rate and their odds as well as the proportion of the population expected to test positive to the condition in the screening test which are additional useful information to guide policy formulation and implementation over and above the traditional odds ratio method. Modified estimates of the standard deviation and test statistic for the proposed measure that adjust for the fact that some sample observations in a screening test are not known and cannot therefore validly be used in traditional relative risk estimation method are provided. The proposed method which is shown to provide more information and to be at least as efficient as the traditional relative risk method is illustrated with some sample data.

DOI 10.11648/j.ajbls.20130103.15
Published in American Journal of Biomedical and Life Sciences (Volume 1, Issue 3, October 2013)
Page(s) 64-69
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Chi-Square Test of Independence, False Negative Rate, False Positive Rate, Relative Risk, Specificity, Sensitivity

References
[1] Akobeng AK (2007).Understanding diagnostic tests 2: likelihood ratios, pre- and post-test probabilities and their use in clinical practice. Acta Paediatr 96(4):487-91.
[2] Agresti, A (2007). Introduction to Categorical Data Analysis. John Wiley and Sons. Inc., Publications. New York.
[3] Altman DG (1996). Statistics with Confidence. BMJ Publishing Group. 28-33.
[4] Altman DG., Bland JM (1994). Diagnostic Tests I: Sensitivity and specificity. BMJ, 308(6943):1552. London.
[5] Fleiss JL (1973). Statistical Method for Rates and Proportions. John Wiley, New York.
[6] Gardner MJ, Altman DG (1989). Calculating confidence intervals for proportions and their differences. In: Gardner MJ,
[7] Kestenbaum B (2009). Epidemiology and Biostatistics: an introduction to clinical research. Springer Science LLC.
[8] Lalkhen AG, McCluskey A (2008). Clinical tests: sensitivity and specificity.Continuing Education in Anaesthesia.Critical
[9] Care & Pain J. 8(6): 221-223
[10] Miller J. Statistics for Advanced Level (1996). (2nd Edition) Cambridge University Press
[11] Uche PI (2004). Probability: Theory and Practice. Longman Nig PLC
[12] Zweig MH, Ashwood ER, Galen RS, Plous RH, Robinowitz M (1995). Assessment of the Clinical Accuracy of LaboratoryTests Using Receiver Operating Characteristics (ROC) Plots; Approved Guideline. NCCLS Standards and Guidelines.15(19): 1-27
Author Information
  • Department of Applied Statistics, Nnamdi Azikiwe University, Awka Nigeria

  • Department of Industrial Mathematics and Applied Statistics, Ebonyi State University Abakaliki, Nigeria

  • Department of Histopathology,Nnamdi Azikiwe University Teaching Hospital Nnewi Anambra State, Nigeria

  • Department of Opthalmology, Enugu State University Teaching Hospital Park lane Enugu State,Nigeria

  • Department of Haematology, University of Port Harcourt Teaching Hospital, Port Harcourt, Rivers State Nigeria

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    Oyeka Ikewelugo Cyprian Anaene, Okeh Uchechukwu Marius, Igwebuike Victor Onyiaorah, Adaora Amaoge Onyiaorah, Chilota Chibuife Efobi. (2013). Estimating False Rates-Based Relative Risk as Measure of Association in Diagnostic Screening Test. American Journal of Biomedical and Life Sciences, 1(3), 64-69. https://doi.org/10.11648/j.ajbls.20130103.15

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    ACS Style

    Oyeka Ikewelugo Cyprian Anaene; Okeh Uchechukwu Marius; Igwebuike Victor Onyiaorah; Adaora Amaoge Onyiaorah; Chilota Chibuife Efobi. Estimating False Rates-Based Relative Risk as Measure of Association in Diagnostic Screening Test. Am. J. Biomed. Life Sci. 2013, 1(3), 64-69. doi: 10.11648/j.ajbls.20130103.15

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    AMA Style

    Oyeka Ikewelugo Cyprian Anaene, Okeh Uchechukwu Marius, Igwebuike Victor Onyiaorah, Adaora Amaoge Onyiaorah, Chilota Chibuife Efobi. Estimating False Rates-Based Relative Risk as Measure of Association in Diagnostic Screening Test. Am J Biomed Life Sci. 2013;1(3):64-69. doi: 10.11648/j.ajbls.20130103.15

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  • @article{10.11648/j.ajbls.20130103.15,
      author = {Oyeka Ikewelugo Cyprian Anaene and Okeh Uchechukwu Marius and Igwebuike Victor Onyiaorah and Adaora Amaoge Onyiaorah and Chilota Chibuife Efobi},
      title = {Estimating False Rates-Based Relative Risk as Measure of Association in Diagnostic Screening Test},
      journal = {American Journal of Biomedical and Life Sciences},
      volume = {1},
      number = {3},
      pages = {64-69},
      doi = {10.11648/j.ajbls.20130103.15},
      url = {https://doi.org/10.11648/j.ajbls.20130103.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajbls.20130103.15},
      abstract = {This paper proposes false-rates-based relative risk-type measure of the strength of association between state of nature or condition in a population and test results in diagnostic screening tests. The adopted method provides an estimate for the proposed relative risk that depends only on the estimated sensitivity and specificity of the test in the event that the prevalence rate is not known. The proposed method unlike the traditional odds ratio provides estimates of not only the proposed false rates based relative risk-type measure of association, but also alternative sample estimates of its associated standard deviation and test statistic for significance that intrinsically and structurally partials out, that is, does not include in its formulation the number of subjects in the sample known or believed to actually have the condition in nature but test negative or actually do not have the condition in nature but test positive to the condition in the screening test. The proposed method given that the prevalence rate of the condition in the population is known, provides sample estimates of the false positive rate, false negative rate and their odds as well as the proportion of the population expected to test positive to the condition in the screening test which are additional useful information to guide policy formulation and implementation over and above the traditional odds ratio method. Modified estimates of the standard deviation and test statistic for the proposed measure that adjust for the fact that some sample observations in a screening test are not known and cannot therefore validly be used in traditional relative risk estimation method are provided. The proposed method which is shown to provide more information and to be at least as efficient as the traditional relative risk method is illustrated with some sample data.},
     year = {2013}
    }
    

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    T1  - Estimating False Rates-Based Relative Risk as Measure of Association in Diagnostic Screening Test
    AU  - Oyeka Ikewelugo Cyprian Anaene
    AU  - Okeh Uchechukwu Marius
    AU  - Igwebuike Victor Onyiaorah
    AU  - Adaora Amaoge Onyiaorah
    AU  - Chilota Chibuife Efobi
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    T2  - American Journal of Biomedical and Life Sciences
    JF  - American Journal of Biomedical and Life Sciences
    JO  - American Journal of Biomedical and Life Sciences
    SP  - 64
    EP  - 69
    PB  - Science Publishing Group
    SN  - 2330-880X
    UR  - https://doi.org/10.11648/j.ajbls.20130103.15
    AB  - This paper proposes false-rates-based relative risk-type measure of the strength of association between state of nature or condition in a population and test results in diagnostic screening tests. The adopted method provides an estimate for the proposed relative risk that depends only on the estimated sensitivity and specificity of the test in the event that the prevalence rate is not known. The proposed method unlike the traditional odds ratio provides estimates of not only the proposed false rates based relative risk-type measure of association, but also alternative sample estimates of its associated standard deviation and test statistic for significance that intrinsically and structurally partials out, that is, does not include in its formulation the number of subjects in the sample known or believed to actually have the condition in nature but test negative or actually do not have the condition in nature but test positive to the condition in the screening test. The proposed method given that the prevalence rate of the condition in the population is known, provides sample estimates of the false positive rate, false negative rate and their odds as well as the proportion of the population expected to test positive to the condition in the screening test which are additional useful information to guide policy formulation and implementation over and above the traditional odds ratio method. Modified estimates of the standard deviation and test statistic for the proposed measure that adjust for the fact that some sample observations in a screening test are not known and cannot therefore validly be used in traditional relative risk estimation method are provided. The proposed method which is shown to provide more information and to be at least as efficient as the traditional relative risk method is illustrated with some sample data.
    VL  - 1
    IS  - 3
    ER  - 

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