International Journal of Mathematics Trends and Technology
Volume 65 | Issue 3 | Year 2019 | Article Id. IJMTT-V65I3P501 | DOI : https://doi.org/10.14445/22315373/IJMTT-V65I3P501
Pool testing for presence or absence of a trait is less expensive, less time consum- ing and therefore more cost efiective. This study presents a multi-stage adaptive pool testing estimator ^pn of prevalence of a trait in the presence of test errors. An increase in the number of stages improves the eciency of the estimator, hence con- struction of a multi-stage model. The study made use of the Maximum Likelihood Estimate (MLE) method and Martingale method to obtain the adaptive estimator and Cramer-Rao lower bound method to determine the variance of the constructed estimator. Matlab and R, statistical softwares were used for Monte-carlo simula- tion and verification of the model, then analysis and discussion of properties of the constructed estimator, notably eficiency in comparison with the non-adaptive estimator in the absence of test errors in the literature of pool testing done along- side provision of the confidence interval of the estimator. Results have shown that the eficiency of the multi-stage adaptive estimator in the presence of test errors is higher than that of the non-adaptive estimator in the absence of test errors. This eficiency also increases with increase in sensitivity and specificity of the test kits. This makes the multi-stage adaptive estimator in the presence of test errors better than the non-adaptive estimator in the absence of test errors, especially so that errors in experiments in our day to day encounters are inevitable.
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Okoth Annette W, "A Multi-Stage Adaptive Pool Testing Model with Test Errors Vis-a-Vis the Non-Adaptive Model without Test Errors," International Journal of Mathematics Trends and Technology (IJMTT), vol. 65, no. 3, pp. 1-15, 2019. Crossref, https://doi.org/10.14445/22315373/IJMTT-V65I3P501
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