it, but is there a
mathematical solution?
Many thanks
Eleni Rapsomaniki
Medical Statistician
UCL, London
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one
plots the fitted function results are just as hard to interpret. That's
why the simultaneous CI plot will be very useful.
Eleni
On Jan 9, 2012, at 8:45 AM, Eleni Rapsomaniki e.rapsoman...@ucl.ac.uk
wrote:
Dear R users,
The package 'mfp' that fits fractional polynomial terms to predictors
Hi,
The mfp package suggests fractional polynomial transformations for
non-linear predictors. For continuous variables that take negative values
the suggested transformations tend to look ugly, e.g. if x1 is the
original variable it is transformed to something like: (x1+5.67)^1 *
log(x1+5.67),
data (counting)
fit2 - coxph(Surv(age,age+time2, status) ~ ph.ecog
+ph.karno+pat.karno+meal.cal+wt.loss + age + sex, lung2)
survConcordance(Surv(time, status) ~predict(fit2), lung2)
Many thanks
Eleni Rapsomaniki
Research Associate
Department of Public Health and Primary Care
University
0
This is a potentially very useful function so it would be great if someone
could explain the behaviour here.
Many thanks
Eleni Rapsomaniki
Research Associate/Statistician
Strangeways Research Laboratory
Department of Public Health and Primary Care
University of Cambridge
1.64669e-10
Many thanks for any help you may be able to provide.
Eleni Rapsomaniki
Research Associate
University of Cambridge
Institute of Primary and Public Health
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PLEASE do
=)
#they are superimposed... which is not what I want.
Any hints/ideas much appreciated!
Many thanks
Eleni Rapsomaniki
Research Associate
Department of Public Health and Primary Care
University of Cambridge
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a matrix:
m1=cbind(1:5,1:5,1:5)
#The aim is to create a new matrix with every column containing the cumulative
sum of all previous columns.
m2=m1
for(i in 2:ncol(m1)){
m2[,i]=apply(m1[,1:i],1,sum)
}
m2
Many thanks in advance
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
That's really interesting... I have always assumed that for-loops take
longer than apply. Perhaps it depends on the application. I'll try both
in my code and see.
Thank you!
Eleni Rapsomaniki
Research Associate
Tel: +44 (0) 1223 740273
Strangeways Research Laboratory
Department of Public
observed probabilities). Any other functions I should be aware of?
Also, has anybody come across an implementation of the statistic described in:
A global goodness of fit statistic for Cox regression models by Parzen
Lpisitz, Biometrics 55, 1999
Many thanks in advance
Eleni Rapsomaniki
Research
information than a single statistic anyway!). I will try the updated
version in the rms package to compare.
Best Wishes
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
Department of Public Health and Primary Care
University of Cambridge
-Original Message-
From
, ~ . -A)
#gives me this:
#Surv(time, status) ~ x1 + x2 + x3 + x4 + B + x5 + strata(sex) + A:x3 + A:x4 +
B:x5
#but I want this:
#updated.forml=as.formula(Surv(time, status) ~ x1+x2+x3+x4+B*x5+strata(sex))
Any ideas?
Thanks in advance
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
linear.predictors=) for better estimates.
I would like to turn this specific warning off, as it makes it difficult to
detect other (potentially more crucial) warnings generated by other parts of my
code.
Is there a way to do this?
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
Dear R users,
Is there an R function to compute the pooled mean?
Many Thanks
Eleni Rapsomaniki
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for
either cause (perhaps a parametric model could be used in this case).
But then again, this was not an issue wtih my data.
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
Department of Public Health and Primary Care
University of Cambridge
-Original Message-
From
(people who die
from competing causes remaining in the risk set) are theoretically
sound.
If anybody is interested in the Kalbfleisch Prentice based cumulative
incidence adjusting for competing risks with covariates, I'm happy to
supply the code.
Eleni Rapsomaniki
Research Associate
Tel
Rapsomaniki
Research Associate
Tel: +44 (0) 1223 740273
Strangeways Research Laboratory
Department of Public Health and Primary Care
University of Cambridge
-Original Message-
From: Ravi Varadhan [mailto:rvarad...@jhmi.edu]
Sent: 26 March 2009 14:36
To: Eleni Rapsomaniki; 'Arthur
, cause=k1|x)=Sum(u=0, ..., u=t) {hazard_k(u;x)*S(u;x)}
where S(u;x) = exp{-sum_of_k(sum(hazard_k(u))}
I have searched extensively for an implementation of this in many
packages, but it appears that more complex approaches are more commonly
implemented, such as timereg package.
Eleni
to adjust for more than one covariate (it allows you
to stratify by a single grouping vector).
Any help/tips will be extremely appreciated.
Eleni Rapsomaniki
Research Associate
Cambridge
[[alternative HTML version deleted]]
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computing it myself?
Many Thanks
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
Department of Public Health and Primary Care
University of Cambridge
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rcorr.cens is not meant for that.
Thank you for the clarification. On a second thought, I think (hope) a
time-dependent AUC index should be more appropriate in this case, such
as survivalROC.
Many many thanks for all your help!
Eleni Rapsomaniki
Research Associate
Tel: +44 (0) 1223
do I get the equivalent risks from
the two models?
Any tips greatly appreciated!!
(FYI A related entry to my question can be found at:
http://tolstoy.newcastle.edu.au/R/e2/help/07/02/9831.html)
Eleni Rapsomaniki
Research Associate
Department of Public Health and Primary Care
University
), or hazard
etc, which is what I get from survest and predict for example.
I suspect the answer is embarrassing simple...
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
Department of Public Health and Primary Care
[[alternative HTML version
), or hazard etc,
which is what I get from survest and predict for example.
I suspect the answer is embarrassing simple...
(BTW sorry for the duplicate email, the earlier HTML version of my message
could not be viewed)
Eleni Rapsomaniki
Research Associate
Strangeways Research Laboratory
Department
Hi
I am trying to understand how to get the validate() function in Design
to work with the subset option. I tried this:
ovarian.cph=cph(Surv(futime, fustat) ~ age+factor(ecog.ps)+strat(rx),
time.inc=1000, x=T, y=T, data=ovarian)
validate(ovarian.cph)
#fine when no subset is used, but
Dear R users,
I know one way to see the code for a hidden function, say function_x,
is using default.function_x (e.g. summary.default). But how can I see
the code for imported packages that have no namespace (in this case
Design)?
Many Thanks
Eleni
(time,status) ~ quantile(age,3), data=veteran)
#will not work
ideally I would like to superimpose estimates from cph models, which
automatically fit the 2nd to 4rth quantiles for age, so I need the age
groups to be grouped the same.
Any help greatly appreciated!
Eleni Rapsomaniki
distribution?
Many Thanks in advance,
Eleni Rapsomaniki
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and provide commented, minimal, self-contained
than Excel would be very
much appreciated.
Many Thanks
Eleni Rapsomaniki
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