binomial proportions
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Author(s):  
José Juan Castro-Alva ◽  
Félix Almendra-Arao ◽  
Hortensia Josefina Reyes-Cervantes ◽  
Francisco Solano Tajonar-Sanabria

2021 ◽  
Vol 42 (2) ◽  
pp. 394-403
Author(s):  
A. Kokaew ◽  
J. Thaithanan ◽  
W. Bodhisuwan ◽  
A. Volodin

2021 ◽  
Vol 42 (2) ◽  
pp. 435-450
Author(s):  
Chanakan Sungboonchoo ◽  
Thuntida Ngamkham ◽  
Wararit Panichkitkosolkul ◽  
Andrei Volodin

2020 ◽  
Vol 29 (12) ◽  
pp. 3547-3568
Author(s):  
Shi-Fang Qiu ◽  
Qi-Xiang Fu

This article investigates the homogeneity testing problem of binomial proportions for stratified partially validated data obtained by double-sampling method with two fallible classifiers. Several test procedures, including the weighted-least-squares test with/without log-transformation, logit-transformation and double log-transformation, and likelihood ratio test and score test, are developed to test the homogeneity under two models, distinguished by conditional independence assumption of two classifiers. Simulation results show that score test performs better than other tests in the sense that the empirical size is generally controlled around the nominal level, and hence be recommended to practical applications. Other tests also perform well when both binomial proportions and sample sizes are not small. Approximate sample sizes based on score test, likelihood ratio test and the weighted-least-squares test with double log-transformation are generally accurate in terms of the empirical power and type I error rate with the estimated sample sizes, and hence be recommended. An example from the malaria study is illustrated by the proposed methodologies.


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