Survival analysis with truncated data
I think that your data is censored, not truncated. For a fault introduced 1/2005 and erased 2/2006, duration = 13 months For a fault introduced 4/2010 and still in existence at the last observation 12/2010, duration> 8 months. For a fault introduced before 2004, erased 3/2005, in a machine installed 2/1998, the duration is somewhere between 15 and 87 months. For a fault introduced before 2004, smachine installed 5/2000, still present 11/2010 at last check, the duration is > 126 months. For type=interval2 the data would be (13,13), (8,NA), (15,87), (126, NA). Terry T.
On 11/14/2013 05:00 AM, r-help-request at r-project.org wrote:
Hi, I would like to know how to handle truncated data. My intend is to have the survival curve of a software fault in order to have some information about fault lifespan. I have some observations of a software system between 2004 and 2010. The system was first released in 1994. The event considered is the disappearance of a software fault. The faults can have been introduced at any time, between 1994 and 2010. But for fault introduced before 2004, there is not mean to know their age. I used the Surv and survfit functions with type interval2. For the faults that are first observed in 2004, I set the lower bound to the lifespan observed between 2004 and 2010. How could I set the upper bound ? Using 1994 as a starting point to not seems to be meaningful. Neither is using only the lower bound. Should I consider another survival estimator ? Thanks in advance.