The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Survival Analysis using SRC-Stat Statistical Package

SRC-Stat 통계패키지를 이용한 생존분석

  • Ha, Il Do (Department of Statistics, Pukyong National University) ;
  • Noh, Maengseok (Department of Statistics, Pukyong National University) ;
  • Lee, Youngjo (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Lim, Johan (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Lee, Jaeyong (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Oh, Heeseok (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Shin, Dongwan (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Lee, Sanggoo (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Seo, Jinuk (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Park, Yonhtae (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Cho, Sungzoon (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Park, Jonghun (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Kim, Youkyung (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • You, Kyungsang (Data Science for Knowledge Creation Research Center, Seoul National University)
  • 하일도 (부경대학교 통계학과) ;
  • 노맹석 (부경대학교 통계학과) ;
  • 이영조 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 임요한 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 이재용 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 오희석 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 신동완 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 이상구 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 서진욱 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 박용태 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 조성준 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 박종헌 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 김유경 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 유경상 (서울대학교 데이터과학과 지식창출 연구센터)
  • Received : 2015.03.23
  • Accepted : 2015.03.31
  • Published : 2015.04.30
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Abstract

In this paper we introduce how to analyze survival data via a SRC-Stat statistical package. This provides classical survival analysis (e.g. Cox's proportional hazards models for univariate survival data) as well as advanced survival analysis such as shared and nested frailty models for multivariate survival data. We illustrate the use of our package with practical data sets.

본 논문에서는 SRC-Stat 통계패키지를 이용하여 생존자료를 분석하는 방법을 소개한다. 본 패키지는 단변량 생존 자료 분석을 위한 콕스의 비례위험모형 뿐만아니라, 다변량 생존자료분석을 위한 공통 및 지분 프레일티 모형과 같은 고급 생존분석법을 제공한다. 잘 알려져 있는 실제자료의 사용을 통해 본 패키지의 유용성을 예증한다.

Keywords

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