Ravi Varadhan wrote:
Frank,
Is there an article that discusses this idea of bootstrapping the ranks of
the likelihood ratio chi-square
Statistics to assess relative importance of predictors in time-to-event data
(specifically Cox PH model)?
Thanks,
Ravi.
Do require(rms); ?anova.rms and see related articles:
@Article{hal09usi,
author = {Hall, Peter and Miller, Hugh},
title = {Using the bootstrap to quantify the authority of an
empirical ranking},
journal = Annals of Stat,
year = 2009,
volume = 37,
number = {6B},
pages = {3929-3959},
annote = {confidence interval for ranks;genomics;high
dimension;independent component bootstrap;$m$-out-of-$n$
bootstrap;ordering;overlap interval;prediction interval;synchronous
bootstrap;ordinary bootstrap may not provide accurate confidence
intervals for ranks;may need a different bootstrap if the number of
parameters being ranked increases with $n$ or is large;estimating $m$ is
difficult;in their first example, where $m=0.355n$, the ordinary
bootstrap provided a lower bound to the lengths of more accurate
confidence intervals of ranks}
}
@Article{xie09con,
author = {Xie, Minge and Singh, Kesar and Zhang, {Cun-Hui}},
title = {Confidence intervals for population ranks in the presence
of ties and near ties},
journal = JASA,
year = 2009,
volume = 104,
number = 486,
pages = {775-787},
annote = {bootstrap ranks;ranking;nonstandard bootstrap
inference;rank inference;slow convergence rate;smooth ranks in the
presence of near ties;rank inference for fixed effects risk adjustment
models}
}
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Frank E Harrell Jr
Sent: Tuesday, March 30, 2010 3:57 PM
To: Michal Figurski
Cc: r-help@r-project.org
Subject: Re: [R] Problem comparing hazard ratios
Michal Figurski wrote:
Dear R-Helpers,
I am a novice in survival analysis. I have the following code:
for (i in 3:12) print(coxph(Surv(time, status)~a[,i], data=a))
I used it to fit the Cox Proportional Hazard models separately for every
available parameter (columns 3:12) in my data set - with intention to
compare the Hazard Ratios.
However, some of my variables are in range 0.1 to 1.6, others in range
5000 to 9000. How do I compare HRs between such variables?
I have rescaled all the variables to be in 0 to 1 range - is this the
proper way to go? Is there a way to somehow calculate the same HRs (as
for rescaled parameters) from the HRs for original parameters?
Many thanks in advance.
There are a lot of issues related to this that will require a good bit
of study, both in survival analysis and in regression. I would start
with bootstrapping the ranks of the likelihood ratio chi-square
statistics of the competing biomarkers.
Frank
--
Frank E Harrell Jr Professor and Chairman School of Medicine
Department of Biostatistics Vanderbilt University
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