topic these days (or at least I can't find it). I realize this
is all a bit OT for r-help though...
Dimitris Rizopoulos wrote:
On 2/23/2010 3:37 PM, Philipp Rappold wrote:
I have one more conceptual question though, it would be fantastic if
someone could graciously help out:
I am using a
I have one more conceptual question though, it would be fantastic if
someone could graciously help out:
I am using an accelerated failure time model with time-varying
covariates because I assume that my independent variables have a
different impact on the chance for a failure at different poin
OK - I'll see if I can spare some time on the weekend to dig a bit
deeper and maybe find the issue.
(Unfortunately I cannot use a phreg model because I cannot assume a
proportional hazards assumption.)
Göran Broström wrote:
Philipp Rappold wrote:
Göran, thanks for the update, I'm
Dear all,
does anyone know if it is possible to connect a Windows RExcel
instance to a linux R instance?
Within Rexcel, I find the option "Remote Server Address", but I
wonder what the installation procedure on my linux (ubuntu) R looks
like (if possible at all)?
Thanks
Philipp
__
is this what you're looking for?
test <- data.frame(a=c("x","v"),b=c("n","m"))
test
statquant wrote:
Hello all
I am new in R and so easy stuff are difficult...
let say that I have a list
test <- list(a=c("x","v"),b=c("n","m"))
how can I without a loop get test$a bind with test$b (obviously in
Göran, thanks for the update, I'm just about to install it!
Just wanted to drop you a short line about performance (as you once
requested):
aftreg takes ages on my windows machine to calculate a small set of
7 observations which are not even grouped together by "id". To be a
bit more precise, it
Göran, no worries - your help & advice is already invaluable!
Göran Broström wrote:
2010/2/18 Philipp Rappold :
Göran, David,
in order to adapt aftreg to my needs I wrote a little function that I would
like to share with you and the community.
I once promised to fix this 'asa
Dear all,
does anyone know how I can extract specific p-values for covariates
from an aftreg object? After fitting a model with aftreg I can find
all different variables by using str(), but there's no place where
p-values are kept. The odd thing is that print() displays them
correctly.
EXAM
data <- data[complete.cases(data[non_na_cols]),]
data <- data[complete.cases(data[id]),]
cat("Original Call: ")
print(call)
return(aftreg(formula=formula, data=data, id=data[,id], ...))
}
Hope someone finds this interesting.
All the best
Phi
Sorry guys, but I have another one:
I want to write a function that returns a certain column of a
dataframe. The function accepts two argument: the dataframe and the
name of the column, but the column is not given as a "string" but as
a variable name.
EXAMPLE
--
> testd
Thanks a lot guys,
looks like there are -as usual- a gazillion options ;))
f = function(x, vars) x[complete.cases(x[vars]),] seems to be the
most appropriate in my case though.
Best
Philipp
Benilton Carvalho wrote:
On Thu, Feb 11, 2010 at 4:18 PM, Philipp Rappold
wrote:
Dear all,
I
Dear all,
I have two probably very easy questions:
(1) Is there a way to access certain variables by their string-based
name representation?
Example:
numbers <- c("one", "two", "three")
varname <- "numbers"
print(varname[2])
(2) I need this functionality for a customized na.exclude() functio
with only 7 observations on 2 subjects takes 2 minutes...
Göran Broström wrote:
Philipp Rappold wrote:
Dear all,
I have some trouble using the "id"-argument with aftreg (accelerated
failure time regression analysis from the eha library).
As far as I understand it, the id argument is used
time-dependent covariate), you can use the
jointModel() function from package JM, with the option "weibull-AFT-GH"
for the 'method' argument.
For more information you may have a look at:
http://rwiki.sciviews.org/doku.php?id=packages:cran:jm
I hope it helps.
Best,
D
Dear all,
I have some trouble using the "id"-argument with aftreg (accelerated
failure time regression analysis from the eha library).
As far as I understand it, the id argument is used to group
individuals together if there are time-varying covariates and the
data is arranged in counting pr
Dear all,
I have a simple question: How can I retrieve a list with all
properties of an object?
Example:
If I fit a regression with
model <- coxph(Surv()~...)
I know that I can access the coefficients with
model$coefficients[...] afterwards, but how do I know which other
variables are
great if you could point me in the right
direction (eg. literature, name of method,...).
Thanks a lot for you effort, I highly appreciate it!
All the best
Philipp
Göran Broström wrote:
On Thu, Jan 28, 2010 at 2:32 PM, Philipp Rappold
wrote:
Dear Prof. Broström,
Dear R-mailinglist,
first o
Dear Prof. Broström,
Dear R-mailinglist,
first of all thanks a lot for your great effort to incorporate
time-varying covariates into aftreg. It works like a charm so far
and I'll update you with detailled benchmarks as soon as I have them.
I have one more questions regarding Accelerated Failu
Dear R-community,
Dear Prof. Therneau,
I would like to fit an AFT-model with time-dependent covariates and
right-censored data.
Searching the mailing list for information on the subject, I found some old
posts which said it didn't work back then.
My questions:
(1) Has this kind of fitting al
art
> at study entry in Surv(). For example, if a wear part has been
> used for 5 years before study entry, and "dies" 2 years after,
> the data will look like that:
> start stop status
> 57 1
>
> Hope this helps,
> Arthur Allignol
>
>
> Ph
Hi,
I used ggplot2 for plotting recently, you should give it a try - it's excellent.
http://had.co.nz/ggplot2/
All the best
Philipp
DonkeyRhubarb wrote:
> Hi all,
>
> I am looking to create a pie chart from a given column in a .csv file.
>
> My class variables are as follows:
>
> entry_type
Dear friends,
I have used R for some time now and have a tricky question about the
coxph-function: To sum it up, I am not sure whether I can use coxph in
conjunction with missing covariate data in a model with time-variant
covariates. The point is: I know how "old" every piece that I oberserve
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