Displaying 6 results from an estimated 6 matches for "printfun".
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2009 Feb 03
5
Large file size while persisting rpart model to disk
I am using rpart to build a model for later predictions. To save the
prediction across restarts and share the data across nodes I have been
using "save" to persist the result of rpart to a file and "load" it
later. But the saved size was becoming unusually large (even with
binary, compressed mode). The size was also proportional to the amount
of data that was used to create the
2007 Apr 17
3
Extracting approximate Wald test (Chisq) from coxph(..frailty)
Dear List,
How do I extract the approximate Wald test for the
frailty (in the following example 17.89 value)?
What about the P-values, other Chisq, DF, se(coef) and
se2? How can they be extracted?
######################################################>
kfitm1
Call:
coxph(formula = Surv(time, status) ~ age + sex +
disease + frailty(id,
dist = "gauss"), data = kidney)
2011 Apr 08
1
Variance of random effects: survreg()
I have the following questions about the variance of the random effects in the survreg() function in the survival package:
1) How can I extract the variance of the random effects after fitting a model?
For example:
set.seed(1007)
x <- runif(100)
m <- rnorm(10, mean = 1, sd =2)
mu <- rep(m, rep(10,10))
test1 <- data.frame(Time = qsurvreg(x, mean = mu, scale= 0.5, distribution =
2010 Dec 02
0
survival - summary and score test for ridge coxph()
...quot;
[8] "means" "method" "df" "df2" "penalty" "pterms" "assign2"
[15] "history" "coxlist2" "printfun" "n" "terms" "assign" "wald.test"
[22] "y" "formula" "call"
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2011 Apr 06
1
help on pspline in coxph
Hi there,
I have a question on how to extract the linear term in the penalized
spline in coxph. Here is a sample code:
n=100
set.seed(1)
x=runif(100)
f1 = cos(2*pi*x)
hazard = exp(f1)
T = 0
for (i in 1:100) {
T[i] = rexp(1,hazard[i])
}
C = runif(n)*4
cen = T<=C
y = T*(cen) + C*(1-cen)
data.tr=cbind(y,cen,x)
fit=coxph(Surv(data.tr[,1],
2008 Apr 17
1
survreg() with frailty
Dear R-users,
I have noticed small discrepencies in the reported estimate of the
variance of the frailty by the print method for survreg() and the
'theta' component included in the object fit:
# Examples in R-2.6.2 for Windows
library(survival) # version 2.34-1 (2008-03-31)
# discrepancy
fit1 <- survreg(Surv(time, status) ~ rx + frailty(litter), rats)
fit1
fit1$history[[1]]$theta