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 univariate survival data, but since competing risks events are dependent on each other, if the analysis method of univariate survival data is applied, inferences 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.
Funder
National Research Foundation of Korea
Ministry of Education
Publisher
The Korean Society of Health Informatics and Statistics