SURVIVAL ANALYSIS Meaning and
Definition
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Survival analysis, also known as time-to-event analysis or event history analysis, is a branch of statistics that focuses on the analysis of time until a specific event occurs. It is commonly used in medical research, epidemiology, and social sciences to study and predict the time it takes for individuals in a population to experience an event of interest.
The events under consideration in survival analysis are typically prolonged in nature, such as death, disease recurrence, unemployment, or marriage dissolution. The analysis is concerned with estimating and modeling the probability or hazard of experiencing the event at different time points. Rather than examining the overall survival rate, survival analysis looks into how long it takes for specific events to happen and identifies factors that may influence the timing of these events.
Survival analysis incorporates various statistical techniques, such as Kaplan-Meier estimation, Cox proportional hazards models, and parametric models, to analyze and interpret time-to-event data. It enables researchers to estimate survival functions, hazard rates, and cumulative incidence curves, and further compare survival probabilities between different groups or conditions using log-rank tests or other statistical tests.
By allowing researchers to investigate the timing and impact of events, survival analysis helps in studying disease progression, optimizing treatment strategies, evaluating the effectiveness of interventions, and predicting future outcomes. It provides valuable insights into the dynamics of events in a population over time, thus facilitating informed decision-making in fields where time-to-event data is crucial.
Common Misspellings for SURVIVAL ANALYSIS
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Etymology of SURVIVAL ANALYSIS
The word "Survival Analysis" originated from the field of biostatistics and has its roots in the medical and biological sciences.
The term "survival" in this context refers to the concept of time-to-event analysis, where the event can be the occurrence of a certain event, such as death, disease, recurrence, etc. It focuses on studying the time it takes for an event to happen or for an outcome to occur.
The analysis part of the term refers to the statistical techniques used to analyze and interpret the time-to-event data. These techniques involve a range of mathematical models, such as Kaplan-Meier estimator, Cox proportional hazards model, accelerated failure time models, etc., to estimate survival probabilities, hazard rates, and to assess the impact of various predictors or covariates on the event of interest.
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