[R] Recurrent analysis survival analysis data format question

John Kane jrkrideau at inbox.com
Wed Jun 11 15:12:53 CEST 2014

Hi Chris,
 Why would you not consider the person at risk for re incarceration if he is currently imprisoned?

Symantically I'd agree, he or she is already behind bars.  But from the point of view of extra sentences it is quite possible to commit an offence while in prision and recieve another sequential sentence.  

We have a current case here where three people, already incarcerated, are just been charged with attempted murder.

John Kane
Kingston ON Canada

> -----Original Message-----
> From: chrisaa at med.umich.edu
> Sent: Tue, 10 Jun 2014 19:02:30 +0000
> To: bgreen at dyson.brisnet.org.au
> Subject: Re: [R] Recurrent analysis survival analysis data format
> question
> I wouldn't consider the person at risk for re incarceration if he is
> currently imprisoned.  So I wouldn't use those intervals as part of the
> response variable.  Perhaps time in custody would be a covariate used to
> model the time until re incarceration.  One variable that is commonly
> needed for analysis of recurrent data is the number of previous events.
> It can be used to, e.g., stratify.
> Chris
> -----Original Message-----
> From: Bob Green [mailto:bgreen at dyson.brisnet.org.au]
> Sent: Tuesday, June 10, 2014 2:32 AM
> To: r-help at r-project.org
> Subject: [R] Recurrent analysis survival analysis data format question
> Hello,
> I'm hoping for advice regarding how to set up a recurrent event
> survival analysis data file. My data consists of people released from
> custody, with survival time being measured as days before re
> imprisonment or end of the study. In the example below, id 5155 is
> released 5 times and jailed five times. All events are therefore
> true. Daysfree is the difference in days between release and return
> to custody.  Id 7155 is released 3 times and only re-imprisoned
> twice, so the third event value is false.
> id <- c(5155, 5155,5155,5155, 7155, 7155,7155)
> Release <- c("29/10/10","9/01/11", "25/03/12", "15/10/13", "9/01/10",
> "16/12/12","29/10/13")
> JailNew <- c("1/12/10","01/12/11", "27/09/12", "24/01/14",
> "22/09/12","24/01/12","24/01/14")
> DaysFree <- c(24,234,134,74,709,29,64)
> Event <- c("true", "true", "true", "true", "true", "true", "false" )
> DF1<- data.frame(id,  Release, JailNew, DaysFree, Event)
> DF1
>   After speaking to a statistician today I'm not sure if I my method
> of formatting the data is correct. Should all time intervals be
> included, not just the period from release to event/end of study
> period.  Currently period imprisoned is not counted.  For example,
> for id 5155, would I also include  1/12/10 - 9/01/11 etc, which would
> be FALSE for event and have a duration of 39 days; and then include
> all the other similar intervals as well. The statistican thought
> including this additional information more closely resembled the
> bladder1 data in the Survival package.
> Any assistance is appreciated,
> Regards
> Bob
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