Measure of Association Dependent on Sensitivity and Specificity of Diagnostic Screening Tests in a Study Population


  • Okey UM Department of Industrial Mathematics,David Umahi Federal University of Health Sciences Uburu Ebonyi State Nigeria
  • Okoro CN Department of Industrial Mathematics and Applied Statistics, Ebonyi State University Abakaliki, Ebonyi State, Nigeria.



sensitivity, specificity, traditional odds ratio, diagnostic screening tests, state of nature or condition, clinical trial


Background: The traditional odds ratio and relative risk cannot strictly speaking properly and validly be used because in them, the number of subjects testing positive and negative among subjects known or believed not to have a condition in nature usually are not known and hence the total number of subjects testing positive and negative are not also completely known. Paper proposes, develops, and presents a measure of the strength of association between test results and condition in a population, by using sensitivity and specificity of diagnostic screening tests that are independent of the population under study.

Method: A retrospective study was carried out. The proposed measure of association which always lies between -1 and 1 inclusively enables the researcher to determine not only if an association exists between test results and state of nature or condition in a population and if such an association exists, whether it is positive and direct or negative and indirect thereby giving the measure an advantage over and above the traditional odds ratio method.

Result: The proposed method is easier to interpret and understand than those from the traditional odd ratio approach. For comparison and completeness, it also develops modified sample estimate of the traditional odd ratio and its sample variance from observable sample data. The likelihood ratio showed that the test is very informative.

Conclusion: The proposed measure of association is shown to be at least as efficient and hence as powerful as the traditional odds ratio. The modified traditional odds ratio performs better than the traditional odds ratio. The likelihood ratios are at least as efficient as the proposed method but better than the traditional odd ratio.


Raffles A, Mackie A, Muir Gray JA. Screening: evidence and practice. 2nd ed. Oxford: Oxford University Press. 2019

Rosner B. Fundamentals of biostatistics. 8th ed. Boston: Brooks Cole, Cengage Learning. 2015.

Fleiss JL,Bruce Levin and Myunghee Cho Paik.. Statistical Method for Rates and proportions (3rd ed), Wiley Interscience, New Jersey. 2003.

Li J, Fine JP. Assessing the dependence of sensitivity and specificity on prevalence in meta-analysis. Biostatistics. 2011; 12:710-22.

Agresti AA. An Introduction to Categorical Data Analysis (Wiley Series in Probability and Statistics) 3rd Edition. New York: Wiley. 2019

Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford statistical series 28, Oxford: University Press, U.K; 2003

Naeger DM, Kohi MP, Webb EM, Phelps A, Ordovas KG, Newman TB. Correctly using sensitivity, specificity, and predictive values in clinical practice: how to avoid three common pitfalls. AJR Am J Roentgenol. 2013; ;200(6): W566-70.

Bartol T. Thoughtful use of diagnostic testing: Making practical sense of sensitivity, specificity, and predictive value. Nurse Pract. 2015; ;40(8):10-2.

Baron JA. Clinical epidemiology, in Teaching Epidemiology eds. Olsen J; Saracci R; and Trichopoulos D; Oxford: Oxford University Press, 2001; 237-249.

Leeflang MM, Rutjes AW, Reitsma JB, Hooft L, Bossuyt PM. Variation of a test’s sensitivity and specificity with disease prevalence. Cmaj. 2013;185(11): E537-44.

Perry GP, Roderer NK and Asnar SA. Current perspective of medical informatics and health sciences librarianship. J Med Libr Assoc. 2005; 33:199–206.

Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. Journal of clinical epidemiology. 2005;58(10):982-90.

Ma X, Nie L, Cole SR, Chu H. Statistical methods for multivariate meta-analysis of diagnostic tests: an overview and tutorial. Statistical methods in medical research. 2016 Aug;25(4):1596-619.

Oyeka IC, Umeh EU. Measuring strength of association in repeated samples. African Journal of Mathematics and Computer Science Research. 2012;5(14):274-7.

Glasziou P, Hilden J. Test selection measures. Med Decis Making 1989;9(2):133–41.

Kraemer HC. Risk ratios, odds ratio, and the test QROC. In: Evaluating medical tests. Newbury Park, CA: SAGE Publications, Inc.; 1992; 103–13.

Hlatky MA, Lee KL, Botvinick EH, Brundage BH. Diagnostic test use in different practice settings. A controlled comparison. Arch Intern Med 1983;143(10):1886–9.




How to Cite

Okeh, U., & Okoro, C. (2024). Measure of Association Dependent on Sensitivity and Specificity of Diagnostic Screening Tests in a Study Population . The Nigerian Health Journal, 24(1), 1099–1108.

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.