[R] Recurrent analysis survival analysis data format question

bgreen at dyson.brisnet.org.au bgreen at dyson.brisnet.org.au
Wed Jun 11 17:46:27 CEST 2014


Hello Chris,

Thanks. This is not as straight forward as it seems.

Given an index release date, I have dates of prior and subsequent
imprisonment, offending that results in re-incarceration and hospital
admission dates, pre and post.

There are some additional complexities, such as people released from
custody straight to a psychiatric hospital, and transfers the other way,
which can inflate the recidivism rates.

Regards

Bob


> Hi John,
> That must be in Canada, where everyone is a thug, unlike here in the US.
> :-)
>
> But seriously, you make a good point.  I guess it depends on what the
> event variable is: commission of a new crime, start of a new sentence,
> reincarceration after a period of freedom, etc. (and what data Bob has).
> If a person is found guilty of two crimes (e.g. two robberies in a single
> spree) and the jail terms are to be served consecutively, is that one
> event or two?
>
> Chris
>
> -----Original Message-----
> From: John Kane [mailto:jrkrideau at inbox.com]
> Sent: Wednesday, June 11, 2014 9:13 AM
> To: Andrews, Chris; Bob Green
> Cc: r-help at r-project.org
> Subject: Re: [R] Recurrent analysis survival analysis data format question
>
> 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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