Examples Of Abstract Survival Analysis

Abstract Survival analysis is normally used to describe the analysis of data that depend on the time between constant starting point until the occurrence of specific event or endpoint. There are certain aspects of the survival analysis data, such as censoring and non-normality, which can generate great difficulty when trying to analyze data using traditional statistical models. In this paper, the Kaplan-Meier estimator is used to estimate the survival function. Also, Log-Rank test is used to compare between groups using the stages of the illness as comparing factors. Finally, Cox’s regression model is one of the most applied methods in medical research, is used to determine the factors that affect the survival time and assess the relative risks.

diagnosis of deadly diseases, until the occurrence of a specific event i.e. death or endpoint. Survival analysis is called reliability analysis in engineering, duration analysis in economics, event history analysis in sociology and medical researchers give it the name of survival analysis. Survival analysis is used because the survival data are generally not symmetrically distributed, so it can not follow the normal distribution. The survival data depend on the time and it render standard methods in which the survival times are frequently censored. There are three reasons of censoring, first the study end and the patient still alive, second a patient is lost to follow-up during the study period, and finally, if a patient is experience event but not the event of interest (i.e. if death is not the event of the interest). There are three types of censoring, right, left and interval censoring. Moreover, the feature that characterizes such data is that the event not necessarily has occurred in all patients when the time of study ends. In addition, full survival time for patients can be unknown. The survival time often called a failure time or event time is a time interval between a starting point and a subsequent event (for example in breast cancer study, patients were followed for five-year from date of

Probably it originated centuries ago, but only after world war II a new era of survival analysis has emerged, being stimulated by an interest in the reliability of military equipment. Previously, the survival analysis term used to refer to an event of death, but, recently the scope of the survival analysis has become widespread. The scientists are using survival analysis in medical research, experimental studies, a psychological experiment, and lifetimes of industrial and so on. Common event studied are death, disease, relapse, and recovery. The studies that used survival analysis as statistical method include studies in breast cancer patients, leukemia patients, and heart