From: Terry Therneau <therneau_at_mayo.edu>

Date: Thu, 10 Apr 2008 08:09:34 -0500 (CDT)

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 10 Apr 2008 - 13:32:55 GMT

Date: Thu, 10 Apr 2008 08:09:34 -0500 (CDT)

Any help will be highly appreciated.

The functions for population expected survival are designed for just this problem, i.e., those that use the US death rate tables. Under the assumption that the second (grouped data set) has a much larger sample size than the first (sample) data:

For each subject in sample 1, compute the expected number of events for that subject, using the rates found in sample 2 = (time at risk) * (rate during that time). For population rate tables this turns out to be a sum: the external rates are a function of age so one gets ......+ (# days at age 55)*(rate for 55 year olds) + (# days at age 56)*(rate for 56 year olds) + .... Call the result "expected", a vector with one element per subject.

Now fit a Poisson model with offset(log(expected)) as one of the predictors. This is a proportional hazards model, with the usual Cox baseline hazard lambda_0 replaced by the known hazard function from sample 2.

Terry Therneau

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 10 Apr 2008 - 13:32:55 GMT

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