On Sep 28, 2011, at 10:56 AM, Ruth Arias wrote:



hallo terry:

I attached araceae data set,

The usual survival analysis via the Kaplan-Meier method only make estimates at the time of events. When you tabulate your data, you see that there were no events for the missing (starting) "time" rows in those categories during the intervals that you are questioning as missing:

xtabs( ~ time+time2+categoria+event, data=araceae)
, , categoria = C, event = 0

      time2
time   2005 2006 2007 2008 2009 2010
  2004    0   23    1    3    1   22
  2005    0    0    0    0    0    0
  2007    0    0    0    0    4   19
  2008    0    0    0    0    0    0
  2009    0    0    0    0    0    0

, , categoria = E, event = 0

      time2
time   2005 2006 2007 2008 2009 2010
  2004    0   22    0    7    3   21
  2005    0    0    1    1    0    0
  2007    0    0    0    0    0   29
  2008    0    0    0    0    0    0
  2009    0    0    0    0    0    1


, , categoria = C, event = 1

      time2
time   2005 2006 2007 2008 2009 2010
  2004    0    5    2    3    0    3
  2005    0    0    0    0    0    0
  2007    0    0    0    2    3    2
  2008    0    0    0    0    1    0
  2009    0    0    0    0    0    0

, , categoria = E, event = 1

      time2
time   2005 2006 2007 2008 2009 2010
  2004    7    2    1    1    3    4
  2005    0    0    0    1    0    0
  2007    0    0    0    3    1    3
  2008    0    0    0    0    0    0
  2009    0    0    0    0    0    0


when I use this:

surara<-survfit(Surv(time,time2,event)~categoria)

Call: survfit(formula = Surv(time, time2, event) ~ categoria)

            records n.max n.start events median 0.95LCL 0.95UCL
categoria=C      94    63       0     21     NA      NA      NA
categoria=E     111    77       0     26     NA      NA      NA
summary(surara)
Call: survfit(formula = Surv(time, time2, event) ~ categoria)

                categoria=C
time n.risk n.event entered censored survival std.err lower 95% CI upper 95% CI 2006 63 5 0 23 0.921 0.0341 0.856 0.990 2007 35 2 30 1 0.868 0.0483 0.778 0.968 2008 62 5 1 3 0.798 0.0536 0.700 0.910 2009 55 4 0 5 0.740 0.0570 0.636 0.861 2010 46 5 0 41 0.660 0.0611 0.550 0.791

                categoria=E
time n.risk n.event entered censored survival std.err lower 95% CI upper 95% CI 2005 71 7 3 0 0.901 0.0354 0.835 0.973 2006 67 2 0 22 0.875 0.0391 0.801 0.955 2007 43 1 36 1 0.854 0.0432 0.774 0.943 2008 77 5 0 8 0.799 0.0469 0.712 0.896 2009 64 4 1 3 0.749 0.0502 0.657 0.854 2010 58 7 0 51 0.658 0.0545 0.560 0.774

You see that your first survfit object is offering a simple sum of 'time2' columns of that tabulation as its 'n.event' values. It's 'n.risk' tabulation is not taking note of whether a case started in any particular prior interval. The n.risk sum appears to be the sum of persons surviving from the prior year less any decedents plus any entrants as reflected in "future" events on that row You notice that there are missing years even in that report: 2004,2005 for category C and 2004 for category E since there are no events in columns for those 'time2' values.


but whe I included type=interval,

suraraint<- survfit(Surv(time,time2,event,type='interval')~categoria) # falta arreglar lo del intervalo!!!
summary(suraraint)
Call: survfit(formula = Surv(time, time2, event, type = "interval") ~
    categoria)

                categoria=C
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
 2004  95.00   13.14    0.862  0.0354        0.795        0.934
 2007  31.86    7.19    0.667  0.0695        0.544        0.818
 2008   1.67    1.67    0.000     NaN           NA           NA

                categoria=E
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
 2004  112.0   18.47    0.835  0.0351        0.769        0.907
 2005   40.5    1.06    0.813  0.0401        0.738        0.896
 2007   37.5    7.46    0.651  0.0620        0.540        0.785


The second object's n.event, when Surv() was constructed with type="interval", has values based on the starting 'time' rows, but I am unable to deduce the estimating algorithm. I remember Therneau saying it wasn't a simple algorithm. The 2008 row in category C has one entry of 1 in the next year and there were no censoring for C- entrants in that year. Why the n.event is 1.67 I cannot say, but at least the n.event does not exceed the n.risk. The code or a copy of Therneau and Grambsch would be sensible places to look for answer by my initial efforts in those direction have not illuminated me.

--
David.


it does not survival calculed for very year

I have a one-year interval between each census



________________________________
De: Terry Therneau <thern...@mayo.edu>
Para: Ruth Arias <rueu...@yahoo.es>
CC: r-help@r-project.org
Enviado: miƩrcoles 28 de septiembre de 2011 16:00
Asunto: Re:  survival analysis: interval censored data

You have still not given me enough information to reproduce your
problem. "Why doesn't it include all years?" I have no way of knowing,
since we have no data.

--- begin included message --
halo david

when I use type= 'interval'

Call: survfit(formula = Surv(ingreso, fecha, estado, type = "interval")
~
    categoria)

and when I use just

Call: survfit(formula = Surv(ingreso, fecha, estado) ~ categoria)

I don t know why when I use type = "interval" it does not survival
calculed for very year


regards<araceae.txt>______________________________________________
R-help@r-project.org mailing list
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.

David Winsemius, MD
West Hartford, CT

______________________________________________
R-help@r-project.org mailing list
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.

Reply via email to