期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2016
卷号：10
期号：9
页码：9-18
DOI：10.14257/ijseia.2016.10.9.02
出版社：SERSC
摘要：The survival analysis examines life-time of an item or human being or an animal. For example, 1) employee satisfaction may lie in promotion in a particular company. 2) Similarly, medical researchers are keenly interested in survival of patients by giving an excellent treatment for dangerous diseases. 3) For engineering equipment's, reliability, availability of a component or an item plays major role in one of the following replacement policy: i)Individual replacement of an item ii)Group replacement of items iii)both (i) and (ii), to be adopted for the smooth functioning of the system to avoid shut down in a manufacturing company. 4) Some specific examples in medicine are after giving chemotherapy for a particular cancer, the patient lives many years beyond of medical history. As an example, if we know a patient survives 60 months and is then censored, use is made of the fact that the patient lived during the first 60 months. After the time of censoring, the censored value is dropped from any survival calculations. Considering our example, we don't know how much beyond 60 months the patient survived, so this data is not used in calculating the survival function beyond that point. In this way survival analysis makes use of censored data. In both survival tables and plots, censored events are noted. In this paper, we wish to build prediction model for the survival of a particular item or human being. We use Kaplan- Meir Method (KMM) to study the same.
