search for: survit

...1460), t=c(365,730,1095,1460,3000), d=c(0,0,0,0,0), x1=c(0,0,0,0,0), x2=c(1.5,1.5,1.5,1.5,1.5)) I think I would need to enter a statement with respect to the frailty term, but I don't know how. Indeed, when I use the survit function with temp data frame, I get an error message: > fit2 <- survfit(model1, newdata=temp, individual=TRUE) Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : variable lengths differ Thank you very much, giacomo

??? Both ?survit.object (linked in the see also section of ?survfit) and ?summary.survfit give you this information. Do you not know how to use R's help faciities -- in which case you should learn them now; see ?help -- or have I misunderstood your query? Cheers, Bert Bert Gunter "The trouble with havi...

...datasets methods base other attached packages: [1] survival_2.39-5 loaded via a namespace (and not attached): [1] Matrix_1.2-6 splines_3.2.3 grid_3.2.3 lattice_0.20-33 On Sat, Aug 26, 2017 at 7:24 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > ??? > > Both ?survit.object (linked in the see also section of ?survfit) and > ?summary.survfit give you this information. Do you not know how to use > R's help faciities -- in which case you should learn them now; see > ?help -- or have I misunderstood your query? > > Cheers, > Bert > > &gt...

Hi I am not sure hiw to get thr CI from summary function on the survfit object. I can get the percent survival for 2 years from survfit object but I dont get Confidence intervals Could anyone suggest a hint Thanks Adrian [[alternative HTML version deleted]]

...ached packages: > [1] survival_2.39-5 > > loaded via a namespace (and not attached): > [1] Matrix_1.2-6 splines_3.2.3 grid_3.2.3 lattice_0.20-33 > > On Sat, Aug 26, 2017 at 7:24 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: >> ??? >> >> Both ?survit.object (linked in the see also section of ?survfit) and >> ?summary.survfit give you this information. Do you not know how to use >> R's help faciities -- in which case you should learn them now; see >> ?help -- or have I misunderstood your query? >> >> Cheers, &gt...

...e your data set so that you have (time1, time2) pairs, each of which describes the interval of time over which the tag was lost. So an animal first captured at time 10 sans tag would be (0,10); with tag at 5 and without at 20 would be (5,20), and last seen with tag at 30 would be (30, NA). Then survit(Surv(time1, time2, type='interval2') ~ 1, data=yourdata) will give a curve that accounts for interval censoring. As a prior poster suggested, if the times are very sparse then you may be better off assuming a smooth curve. Use the survreg function with the same equation as above; see...