경쟁위험을 가진 생존자료의 분석에 대한 고찰: R 패키지 함수를 중심으로
Analyzing Survival Data with Competing Risks Based on R-packages
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
When it comes to data in survival analysis, it is easy to think of one censored or observed survival time of an individual. In the longitudinal study such as a clinical trial, an individual may be simultaneously exposed to different types of events. It is easy to think of competing risks data as an extension of uni- variate survival data, but since competing risks events are dependent on each other, if the analysis method of univariate survival data is applied, infer- ences with bias can be made. In this paper, we briefly introduce the statistical methods developed to analyze competing risks data and apply them to the real examples using the built-in functions in the R package.
Abstract
When it comes to data in survival analysis, it is easy to think of one censored or observed survival time of an individual. In the longitudinal study such as a clinical trial, an individual may be simultaneously exposed to different types of events. It is easy to think of competing risks data as an extension of uni- variate survival data, but since competing risks events are dependent on each other, if the analysis method of univariate survival data is applied, infer- ences with bias can be made. In this paper, we briefly introduce the statistical methods developed to analyze competing risks data and apply them to the real examples using the built-in functions in the R package.
참고문헌 (12)
- Kaplan EL, "Nonparametric estimation from incomplete observations", J Am Stat Assoc, 53(282), pp.457~481 (1958)[DOI]
- Cox DR, "Regression models and life-tables", J R Stat Soc Series B Stat Methodol, 34(2), pp.187~220 (1972)[DOI]
- Cox DR, "Partial Likelihood", Biometrika, 62(2), pp.269~276 (1975)[DOI]
- Aalen OO, "Survival and event history analysis : a process point of view", pp.271~272 (2000), Springer
- Hougaard P., "Analysis of multivariate survival data", pp.11~14 (2000), Springer
- Kalbfleisch JD, "The statistical analysis of failure time data", pp.247~248 (2002), John Wiley & Sons
- Beyersmann J, "Competing risks and multistate models with R" (2012), Springer
- Geskus RB, "Data Analysis with competing risks and intermediate states", pp.2016, Chapman and Hall
- Andersen PK, "Statistical models based on counting processes", pp.11~14 (1993), Springer
- Beyersmann J, "Time-dependent covariates in the proportional hazards model for competing risks", Biostatistics, 9(4), pp.765~776 (2008)[DOI]
- Fine JP, "A proportional hazards model for the subdistribution of a competing risk", J Am Stat Assoc, 94(446), pp.496~509 (1999)[DOI]
- Ruan PK, "Analyses of cumulative incidence functions via nonparametric multiple imputation", Stat Med, 27(27), pp.5709~5724 (2008)[DOI]