Paper Info
Title
Using a rank-based design in estimating prevalence of breast cancer
Abstract
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 in MSRSS needs around 76% fewer observations than that 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.
Year
DOI
Venue
2022
10.1007/s00500-022-06770-0
Soft Computing
Keywords
DocType
Volume
Breast cancer, Cost-efficient design, Imprecise ranking, Proportion estimation
Journal
26
Issue
ISSN
Citations 
7
1432-7643
0
PageRank 
References 
Authors
0.34
4
2
Name
Order
Citations
PageRank
M. Mahdizadeha100.34
Ehsan Zamanzade202.37