Please enable JavaScript.

Coggle requires JavaScript to display documents.

Survival Analysis - Coggle Diagram

- - - - May lead to problem (biased models), if this is not the case
      - May not be the case: transplant studies, patient may leave because they need another treatment, patients may leave because they got better, administrative reasons
    - - Interval censoring
        
        Malaria example: we know the date between negative and positive, but not a precise date
      - Right - Left
        
        Right: The real value for the variable of interest could not be observed, this may be due to various factors
        
        Left: the beginning of the variable of interest may have been before the current estimate/value
    - - Type I
        
        All have the same censoring time
        
        Example: Patients followed in a study, 40 patients are followed from beggining to end
      - Type II
        
        All start at the same time, but censoring happens after x failures
        
        Following 40 lightbulbs, finish experiment once 5 of them have failed
      - Random
        
        the start times and end times are random
        
        Long studies where the entrance gap of time varies widely, and patients leave due to random reasons or at different times
- - - - 1 - F(t) (probability of death, event, whatever the nature is)
    - - Hazard function
    - - Hazard of event at point t