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Survival analysis

Survival analysis is used to compare independent groups on temporal aspects of outcomes

Survival analysis is used to assess the differences between independent groups on their "time-to-event" or temporal (time) aspects of developing a dichotomous categorical outcome. In order to conduct survival analysis, researchers need comparable independent groups, the outcome, and some sort of time signature associated with developing the outcome. Survival analysis does not have to deal specifically with mortality, but with any kind of dichotomous categorical outcome where temporal aspects are of interest. Survival analysis is popular in medicine for developing longitudinal effects of treatment on survival at one year, three years, five years, and so on.

What type of survival analysis will answer your research question?

Researchers are comparing independent groups on time to a dichotomous categorical outcome event. 
Kaplan-Meier
Researcheres want to control for demographic, clinical, or prognostic variables when comparing independent groups on their time to a dichotomous categorical outcome event.
Cox Regression

Multivariate for Categorical Outcomes
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There are two types of survival analysis: Kaplan-Meier and Cox regression.

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