1.1 Meaning of Survival Analysis in General
Survival analysis is a critical division of statistics used primarily to analyze the anticipated or project period for a pending activity or event to occur, including a malfunction of a system, progression of a disease to a full-blown status, death of biological organisms, and many more. In simple terms, survival analysis is defined as a range of techniques used to analyze data in which the result variable is the timeframe until the incidence of occurrence of an activity or event of interest. The specific event can either be the appearance of a disease, or a divorce, or death, or just any other occurrence. The survival time or time to the event can be calculated in years, months, weeks, days, and hours. In engineering, survival analysis is mostly termed as reliability analysis or reliability theory. In economics, it is referred to as duration modeling or duration analysis, while sociologists commonly refer to it as event history analysis.
The subject of survival analysis essentially attempts to provide potential answers to issues in a population. For example, it can try to find the percentage of a specific populace that can endure a given period, the proportion that can survive, and the exact rate that it will recede. It can as well aim to establish the various causes of failure or death, how particular traits or situations decrease or increase the probability of survival and many others. It is important to note that answering each question requires defining the term “lifetime.” However, for the instance of generational survival, the term death is unequivocal, but for mechanical machine reliability, failure is sometimes not defined clearly. For the latter, there are instances whereby systems encounter partial collapse, and their durations cannot as well be localized. This is ambiguity is also sometimes witnessed in biological systems, with some occurrences like heart attacks taking place partially.
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