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Journal of Statistics and Management Systems Volume 22, 2019 - Issue 8
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Articles

Maximum likelihood estimation for the proportion difference of two-sample binomial data subject to one type of misclassification

Dewi RahardjaU. S. Department of Defense, Fort Meade, MD20755, U.S.ACorrespondence[email protected]
,
Han WuDepartment of Mathematics & Statistics, Minnesota State University, Mankato, MN56001, U.S.A
,
Zhiwei ZhangDepartment of Statistics, University of California Riverside, Riverside, CA92521, U.S.A
&
Andrew D. TiedtU.S. Department of Justice, Washington, DC20530, U.S.A
Pages 1365-1379 | Received 01 Apr 2014, Published online: 04 Dec 2019
 
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Abstract

In this manuscript, we derived three likelihood-based interval estimation methods using a closed-form algorithm for the difference of two independent binomial proportion parameters with one type of misclassification. We acquired an identifiable model by using a double-sampling scheme. We also employed simulations to examine the robustness of our three likelihood-based interval estimation methods and summarize that our modified Wald method implemented to new data with Agresti-Coull type of adjustment performs well and has nominal coverage probabilities. This method was adapted to traffic data for an illustration.

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