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A Small-area Data Analysis for Cancer Registration Data of Busan
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암등록 자료에 대한 부산지역 소지역 분석

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Type
Academic journal
Author
Ahreum Kim (부산대학교병원) Changhoon Kim (부산대학교) Maengseok Noh (부경대학교)
Journal
The Korean Data Analysis Society Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제23권 제4호 KCI Accredited Journals
Published
2021.8
Pages
1,559 - 1,567 (9page)
DOI
10.37727/jkdas.2021.23.4.1559

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A Small-area Data Analysis for Cancer Registration Data of Busan
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Research history (2)

2021

A Small-area Data Analysis for Cancer Registration Data of Busan
Ah ,  eum Kim ,  Changhoon Kim Journal of The Korean Data Analysis Society 2021.08 Academic journal
김아름 통계학과 2021.01 Thesis
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Abstract· Keywords

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Small area estimation is one of the statistical estimation methods when accurate estimation is difficult due to the small number of samples with a small sample size. Small area estimation are necessary for various statistical production and have been studied in various ways. A model-based estimation method, one of the small area estimation methods, is based on parametric models like regression estimation, spatial estimation and so on. In this study, hierarchical generalized linear model with random effect was applied to major cancers like stomach cancer using two types of distribution of random effect in models, respectively. For distribution of random effect, Gaussain or gamma distributions are assumed. For this purpose, the method of classifying the data into small areas of the administrative unit was presented first, and then the results of the model fitting were compared by region. We expect that the estimated random effect from the fitted model can be used as an indicator of small area variability.
#암등록 #다단계 일반화 선형 모형 #변량 효과 #소지역 추정 #cancer registration #hierarchical generalized linear model #random effect #small area estimation

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References (7)

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하일도 / 2011 / Fitting Semi-Parametric Frailty Models with Poisson-Distributed Random Effects / Journal of The Korean Data Analysis Society 13(6):2763~2769 dbpia Y. Lee / 1996 / Hierarchical Generalized Linear Models / Journal of the Royal Statistical Society: Series B (Methodological) 58(4):619~656 Crossref 이상진 / 2019 / Robust Estimation in Generalized Linear Model Using Density Power Divergence / Journal of The Korean Data Analysis Society 21(1):1~10 dbpia 임찬영 / 2021 / 가계 소비지출구조의 패널 분석: 가구주의 노동시장 특성과 근로소득을 중심으로 / Journal of The Korean Data Analysis Society 23(3):1153~1168 dbpia 노맹석 / 2014 / The Extension of REML Algorithm for Hierarchical Generalized Linear Models / Journal of The Korean Data Analysis Society 16(3):1159~1170 dbpia

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