Newcomers - people either new to R or new to survival analysis or both - must find it overwhelming. As well-organized as it is, however, I imagine that even survival analysis experts need some time to find their way around this task view. It is a fantastic edifice that gives some idea of the significant contributions R developers have made both to the theory and practice of Survival Analysis. Looking at the Task View on a small screen, however, is a bit like standing too close to a brick wall - left-right, up-down, bricks all around. ![]() We all owe a great deal of gratitude to Arthur Allignol and Aurielien Latouche, the task view maintainers. CRAN’s Survival Analysis Task View, a curated list of the best relevant R survival analysis packages and functions, is indeed formidable. So, it is not surprising that R should be rich in survival analysis functions. ![]() Today, survival analysis models are important in Engineering, Insurance, Marketing, Medicine, and many more application areas. ![]() Basic life-table methods, including techniques for dealing with censored data, were discovered before 1700, and in the early eighteenth century, the old masters - de Moivre working on annuities, and Daniel Bernoulli studying competing risks for the analysis of smallpox inoculation - developed the modern foundations of the field. With roots dating back to at least 1662 when John Graunt, a London merchant, published an extensive set of inferences based on mortality records, survival analysis is one of the oldest subfields of Statistics.
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