@article{ATM11175,
author = {Zhongheng Zhang},
title = {Statistical description for survival data},
journal = {Annals of Translational Medicine},
volume = {4},
number = {20},
year = {2016},
keywords = {},
abstract = {Statistical description is always the first step in data analysis. It gives investigator a general impression of the data at hand. Traditionally, data are described as central tendency and deviation. However, this framework does not fit to the survival data (also termed time-to-event data). Such data type contains two components. One is the survival time and the other is the status. Researchers are usually interested in the probability of event at a given survival time point. Hazard function, cumulative hazard function and survival function are commonly used to describe survival data. Survival function can be estimated using Kaplan-Meier estimator, which is also the default method in most statistical packages. Alternatively, Nelson-Aalen estimator is available to estimate survival function. Survival functions of subgroups can be compared using log-rank test. Furthermore, the article also introduces how to describe time-to-event data with parametric modeling.},
issn = {2305-5847}, url = {https://atm.amegroups.org/article/view/11175}
}