Many thanks for Your time.
M.P.
On Nov 7, 2012, at 9:59 AM,
Thanks to David Winsemius for the replay. i use the latest update of
Hmisc package and I try as reported in the example:
set.seed(1)
library(survival)
x1 <- rnorm(400)
x2 <- x1 + rnorm(400)
d.time <- rexp(400) + (x1 - min(x1))
cens <- runif(400,.5,2)
death <- d.time <= cens
d.time <- pmin(d.time, cens)
rcorrp.cens(x1, x2, Surv(d.time, death))
but to me it appears that NRI and IDi are not reported in the results:
Dxy S.D. x1 more concordant x2 more concordant
-8.212107e-02 1.370738e-01 4.589395e-01
5.410605e-01
n missing uncensored Relevant
Pairs
4.000000e+02 0.000000e+00 1.100000e+01
4.262000e+03
Uncertain C X1 C X2 Dxy
X1
1.553380e+05 9.920225e-01 9.258564e-01
9.840450e-01
Dxy X2
8.517128e-01
The NRI is not reported but an equivalent measure is. As far as getting
output that is labeled the way you expect it, I also looked at the
PredictABEL::reclassification function help page:
"The function also computes continuous NRI, which does not require any
discrete risk categories and relies on the proportions of individuals
with
outcome correctly assigned a higher probability and individuals without
outcome correctly assigned a lower probability by an updated model
compared with the initial model."
I think that is essentiality what rcorrp.cens is providing, just not with
the labels you expected.
" The function requires predicted risks estimated by using two separate
risk models. Predicted risks can be obtained using the
functionsfitLogRegModel and predRisk or be imported from other methods or
packages."
So it would seem that you could use results from any censored survival
models that had a predict method.
--
David.
but only after:
#rcorrp.cens(x1, x2, y) ## no censoring
set.seed(1)
x1 <- runif(1000)
x2 <- runif(1000)
y <- sample(0:1, 1000, TRUE)
rcorrp.cens(x1, x2, y)
improveProb(x1, x2, y)
thus censoring not allowed. Or I'm in error?
Many thanks
David Winsemius <
On Nov 7, 2012, at 6:54 AM,
Dear all,
I am interested to evaluate reclassification using net
reclassification improvement and Integrated Discrimination Index IDI
after
survival analysis (Cox proportional hazards using stcox). I search a R
package or a R code that specifically addresses the categorical NRI
for
time-to-event data in the presence of censored observation and, if
possible, at different follow-up time points.
I know that the ???PredictABEL??? Package contains functions for NRI
and IDI
calculation but it is unclear for me if it allows censored
observation.
Package ???survIDINRI??? calculates only continuous NRI and the
function of
Package ???Hmisc???[#rcorrp.cens(x1, x2, y) ##] is only for no
censored
observations.
???. Doesn't its name , 'rcorrp.cens' suggest otherwise? Not to mention
its description int the Hmisc Index: "Rank Correlation for Paired
Predictors with a Possibly Censored Response, and Integrated
Discrimination Index". rcoop.cens is a fairly recent addition to Hmisc
and I am looking at Hmisc version 3.10-1. If you are looking at a
version that is a couple of years old, you may be seeing something
different. The argument list you list looks like the one for
improveProb(), which does not appear to handle censoring. The
rcorrp.cens argument list is:
rcorrp.cens(x1, x2, S, outx=FALSE, method=1)
And the "S" object is a Surv-object.
Many thanks.
Sincerely,
Mario Petretta
Dpt. Internal Medicine, Cardiology and Heart Surgery
Naples University Federico II - Italy