Dear useRs,
I was asked to produce a survival curve like this:
http://www.palug.net/Members/jabba/immaginetta.png/view
with the cardinality of the riskset at the bottom.
I do not like doing it, because it doesn't add any valuable information
and because it doesn't discriminate be
Il giorno Thu, 5 May 2011 18:42:11 -0700 (PDT)
Frank Harrell ha scritto:
> Hi Marco,
>
> You're welcome.
>
> The number at risk at given time points is a fairly standard thing to
> add to survival plots.
I know, but last year, as a "newbye" in biostatistics, i felt the need
to read rms book e
Hi Luisa,
it was really difficult to manage to understand what you need. Assuming
that i've done it correctly this should be similar to what you want:
A.matrix <- matrix(rpois(n=28,lambda=2),nrow=7)
M.matrix <- matrix(0,nrow=dim(A.matrix)[2],ncol=dim(A.matrix)[2])
for(i in 1:dim(df)[2])
for(j
>
> Dear Marco,
>
> I was trying using lattice barchart() but your suggestion will do the
> trick.
>
> Many thanks
>
> Javier
Lattice is great but a bit hard for me to learn and customize. I think
you should use ltext() in this case or edit panel.barchart() by hand,
but I don't know how.
DeaR users.
These days i'm working on fitting an extended Cox model with
time-dependent covariables and possibly time-varying effects. My
data are in counting process format as described in Therneau&Grambsh's
`Modeling Survival Data', page 68. I'm trying to follow Harrell's
`Regression Modeling
t with Emacs and ESS, a whole lot more.
>
> Tyler
I agree. In the meantime you learn emacs ;-), cosider using this functions:
getwd()
setwd()
save.image()
install.packages()
and you can install Rmdr and run
library(Rcmdr)
Anyway, I prefer GNU Emacs + ESS, but it can take a bit more time t
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