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Survival analysis is analyzing data to observe the time until the occurrence of a certain event. For example, in clinical trials, we can use survival analysis to analyze whether individuals on the new drug survived longer than individuals on a placebo. Furthermore, this has relevance to real data situations in which physicians or scientists have data where it is desired to have observed an event twice before determining that something meaningful has occurred. Therefore, we created a new survival analysis method for data wherein an "event" was defined as the occurrence of two consecutive events. For the first half of Summer Fellows, I gained understanding of survival analysis in its original form by reading about the topic and doing some programming in R. Then, for the second half, I began to simulate data for our outcome of interest defined as the occurrence of an event at two consecutive time points, and formulate a statistical testing regime for analyzing these data under a modification of traditional survival analysis methods.
Rathod, Faraha, "A Novel Survival Analysis Method for an Outcome of Time to Consecutive Events" (2018). Mathematics Summer Fellows. 9.
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