I am trying to compare the survival in a group of patients with a specific condition to that of age and gender matched U.S. population. I am wondering if there is an easy way to do this in JMP. Any assistance would be greatly appreciated. Thanks!
The survival launch window has a "grouping" option that would compare the survival of the "sample" population to the survival of the "standard" population. Here is a link to an example in the documentation:
This would not be paired by the individual pairs of matched samples but would look at the two groups as a whole. Is this what you are looking for?
Thanks for the reply! I was more wondering with regard to the handling of the different data types. I have used that grouping function to perform survival analysis between different samples in which we have data for each individual. The problem I have is in comparing the survival with an expected survival for a specific population. For example, I want to know if my sample population consisting of all males with a mean age of 50 has a different survival curve from that of the general population that age and gender. This analysis is more complicated than I have done before because I am trying to compare individual sample data with collective population data. In one case, I have the date of birth and the date of death for each person. In the other case, I have just the death rate for people of the same age and gender.
Could it be "as simple" (nothing is simple) as comparing the rate that you have to your estimate from your population using confidence intervals? If your median life time is 80 years (75, 85) and the WHO lifetime is 90 years then your lifetime is shorter, if the WHO is 83 then no different?
In other words, you have an estimate from WHO but no raw data. For your sample you have raw data from which to generate your estimate. Then you need a way to compare the two estimates. I like the confidence interval approach, maybe someone who has done more survival analysis than me will have another idea for you.