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
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
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
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
>
> 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.
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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