“School of Mathematics”
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| Paper IPM / M / 16930 |
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| Abstract: | |
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It is highly important for governments and health organizations to monitor the prevalence of breast cancer as a leading
source of cancer-related death among women. However, the accurate diagnosis of this disease is expensive, especially in
developing countries. This article concerns a cost-efficient method for estimating prevalence of breast cancer, when diagnosis
is based on a comprehensive biopsy procedure. Multistage ranked set sampling (MSRSS) is utilized to develop a proportion
estimator. This design employs imprecise rankings based on some visually assessed cytological covariates, so as to provide
the experimenter with a more informative sample. Theoretical properties of the proposed estimator are explored. Evidence
from numerical studies is reported. The developed procedure can be substantially more efficient than its competitor in simple
random sampling (SRS). In some situations, the proportion estimation inMSRSS needs around 76that in SRS, given a precision level. Thus, using MSRSS may lead to a considerable reduction in cost with respect to SRS. In
many medical studies, e.g., diagnosing breast cancer based on a full biopsy procedure, exact quantification is difficult (costly
and/or time-consuming), but the potential sample units can be ranked fairly accurately without actual measurements. In this
setup, multistage ranked set sampling is an appropriate design for developing cost-efficient statistical methods.
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