# Re: st: Interpretation of sts list

 From Steven Joel Hirsch Samuels To statalist@hsphsun2.harvard.edu Subject Re: st: Interpretation of sts list Date Wed, 14 Nov 2007 22:21:56 -0500

To add to Svend's explanation: Your calculation 17/48 assumes that all 48 people were at risk for the full study period--to 39 days. Not all were. For example, 2 of 48 failed between 1 and 5 days, but only 42 were at risk at 5 days. That means that 4 people (48 - 2 -42) had observation end during the period while still alive. These are referred to as 'censored'. So, you cannot use all 48 as the denominator for failure. Call Duke's Dept of Biostatistics and Informatics, and I am sure someone will take you through the basic calculations.. A couple of online resources are:

http://socserv.mcmaster.ca/jfox/Courses/soc761/survival-analysis.pdf
http://www.statsoft.com/textbook/glosc.html#Censoring

The topic is covered, as Sven states, in almost every biostatistics book.

On Nov 14, 2007, at 4:16 PM, Christina M Gibson-Davis wrote:

Hello,
I am having difficulty interpreting the "survivor function" column of sts list. I had thought it reported the percentage of cases that had survived during a particular time interval, and thus it would be possible to tell, by looking at the last entry, how many cases had survived without failing. However, by using the cancer data available through Stata (webuse cancer), I see that this cannot be.

If I type:
webuse cancer
stset study died
stdes

I see that there are 48 subjects, and 31 failed, for a survival rate of 35% (48-31=17; 17/48 = 35%).

But if I type "sts list, at(0 5 to 39)", I end up with a survival rate of 19% (please see below).

Beg. Survivor Std.
Time Total Fail Function Error [95% Conf. Int.]
---------------------------------------------------------------------- ---------
1 48 2 0.9583 0.0288 0.8435 0.9894
5 42 6 0.8333 0.0538 0.6943 0.9129
9 32 6 0.7061 0.0661 0.5546 0.8143
13 24 6 0.5628 0.0742 0.4060 0.6931
17 20 3 0.4870 0.0761 0.3326 0.6249
21 16 0 0.4870 0.0761 0.3326 0.6249
25 10 6 0.2922 0.0767 0.1543 0.4449
29 8 1 0.2557 0.0753 0.1247 0.4093
33 4 1 0.1918 0.0791 0.0676 0.3634
37 2 0 0.1918 0.0791 0.0676 0.3634
---------------------------------------------------------------------- ---------

I don't understand why the survivor function doesn't end up at 35%, if overall, 35% of the cases survived.

Christina

___________________________________________

Christina Gibson-Davis
Assistant Professor of Public Policy
Center for Child and Family Policy
Terry Sanford Institute
Duke University
Box 90245
Durham NC 27708
cgibson@duke.edu
(919) 613-7364

The thing that impresses me the most about America is the way parents obey
their children.
-- King Edward VIII
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