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| http://dx.doi.org/10.1007/s40122-024-00594-6 | DOI Listing |
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Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing211166, China China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing211166, China.
Extremely unbalanced data refers to datasets with independent or dependent variables showing severe imbalances in proportions, which might lead to deviation of classical test statistics from theoretical distribution and difficulties in controlling type Ⅰ error. The increased availability of genome-wide resources from large population cohorts has highlighted the growing demand for efficient and accurate statistical methods for the process of extremely unbalanced data to improve the development of genetic statistical methods. This paper introduces two widely used correction methods in current genome-wide association study for extremely unbalanced data, i.
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