Literature DB >> 27867953

Statistical description for survival data.

Zhongheng Zhang1.   

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.

Keywords:  Kaplan-Meier; Survival analysis; log-rank; parametric model

Year:  2016        PMID: 27867953      PMCID: PMC5107407          DOI: 10.21037/atm.2016.07.17

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


  6 in total

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Review 6.  Finite sample pointwise confidence intervals for a survival distribution with right-censored data.

Authors:  Michael P Fay; Erica H Brittain
Journal:  Stat Med       Date:  2016-02-18       Impact factor: 2.373

  6 in total
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