生存分析文档

生存分析(Survival analysis)是指根据试验或调查得到的数据对生物或人的生存时间进行分析和推断，研究生存时间和结局与众多影响因素间关系及其程度大小的方法，也称生存率分析或存活率分析。 　　
生存分析涉及有关疾病的愈合、死亡,或者器官的生长发育等时效性指标。 　　
某些研究虽然与生存无关，但由于研究中随访资料常因失访等原因造成某些数据观察不完全,要用专门方法进行统计处理,这类方法起源于对寿命资料的统计分析,故也称为生存分析。

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Event history data is common in many disciplines and at its core, is focused on time. Analysis of event history data or survival analysis is used to refer to a statistical analysis of the time at which the event of interest occurs (Kalbfleisch and Prentice, 2002 and Allison, 1995). Event history data can be categorized into broad categories: 1. longitudinal data, 2. administrative follow-up data, and 3. retrospective event history data.

Longitudinal data is prospectively collected on individuals followed over time. One example is the Panel Study for Income Dynamics, an ongoing US panel study focused on income dynamics and related topics

Administrative follow-up data comes from a study that collects administrative records and additional survey data for a sample of respondents and then prospectively follows those individuals to a key event such as death by linking to another data source. An example of this type of data might be a medical claims data set that is linked to a mortality
data set using respondent Social Security Numbers. The linked files would provide an opportunity to study time to death using a survival analysis approach. An example of this type data is the NHANES III linked mortality file

The third category is retrospective event history data where respondents are asked to recall details about an event of interest which occurred at some point in the past. An example of this type of data is the National Comorbidity Survey-Replication survey  which contains retrospective data on mental illness and related physical conditions.

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