인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국통계학회 CSAM(Communications for Statistical Applications and Methods) CSAM(Communications for Statistical Applications and Methods) 제33권 제3호
- 발행연도
- 2026.5
- 수록면
- 375 - 387 (13page)
이용수
초록· 키워드
Breast cancer is the most diagnosed cancer and the second most common cause of morbidity and mortality among women in the United States. Despite the substantial progress in reducing breast cancer mortality in the US over the past decades, disparities are still exit, especially among Black women. Continued surveillance and the study of breast cancer are essential to monitor progress, evaluate policies, and inform cancer control strategies. However, a complete and clean data set is sometimes unavailable for analysis despite every effort, posing challenges in the study and negatively affecting decision making in the related areas. The breast cancer mortality rates for the US females by race are obtained from 1990 to 2023 from National Cancer Institute (NCI). In this study, we implement functional data analysis approach to estimate the missing values. The method can estimate the values even when one or few observations are available with high degrees of confidence and the residulas are statistically significant at 0.05 level. The model estimates a continuous decline in the breast cancer mortality rates for Asian Pacific Islander women, while the rates remain stable for black and American Indian/Alaska Native women.
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목차
- Abstract
- 1. Introduction
- 2. Material and Method
- 3. Results
- 4. Discussion
- References
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