As promised earlier, the “special topic” material on Survival Analysis is now available on YouTube in lieu of in-person sessions. Take a look at the Survival Analysis in R Playlist.
Survival analysis deals with data that may have truncated observations, called censored data. A typical example is studying the time until failure of a part in engineering, or failure of a part of the human body in medicine (colloquially known as “disease”). We usually have some accurate data on when the problem occurs until the point that the end of the study is reached. Then we will have some subjects that survived without failure until the end of the study, but we are uncertain just how long they would have lasted until failure. The methods of survival analysis account for this partial uncertainty in the data. R can deal with almost all necessary aspects of survival analysis, but requires some mixing and matching of packages to get the best results, as shown in the videos.