.
But I need to estimator the standard error of the quantile in survival
analysis, because my data is censored.
For example~
T-c(84,240,261,332,348,437,521,565)
S-c(0,1,1,0,1,0,1,0) ##0 for censoed; 1 for event
G-rep(1,8)
ori_s.surv-survfit(Surv(T,S)~G)
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Frank Harrell
Department
= 0.8)
It takes enormously high time for execution, is there anything wrong in
the script?
Suggest any other similar function available for dropping redundant
variables.
Thanks in advance!
~A
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is significant (for 10 observations it
should be above 0.64)
Can someone help with this?
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' ), lp=F,
fun.at=c(at.surv, at.surv),label.every=1, force.label=FALSE, cex.axis=0.8,
verbose=TRUE, cex.var=0.8)
Thanks
Min
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any assistance in this matter.
Thank you Very much.
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... does anyone have some
advice on how I might get such a crude method working or must I turn back
and fight with stepAIC?
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=rr1,nboots=1000,data=Passport)
Please suggest me right approach for Propensity score matching using
classification trees(if possible code me) .
ps0-propensity score values
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-Whitney U test.
Frank
Peter Dalgaard-2 wrote
On Jan 12, 2012, at 14:11 , Frank Harrell wrote:
The Kruskal-Wallis test is a special case of the proportional odds
ordinal
logistic model.
Eh? Can you elaborate on that?
I would expect that at best it is equivalent to some _test_ in a polr
This course covers a variety of regression modeling and model validation
methods as well as the R rms package.
Please email interest to eve.a.ander...@vanderbilt.edu
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functions
in S-Plus ever happened.
Frank
Uwe Ligges-3 wrote
On 12.01.2012 17:38, Frank Harrell wrote:
As a slight aside, Tibco/Spotfire originally planned to provide a
capability
to load R packages into S-Plus. This always seemed to me to be a hard
thing
to do, and if my understanding
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(Shells, TotalEggs-Shells) ~
HTL:Veg:TotalEggs:Aeventexhumed, data.to.analyze, family=binomial)
Please advise, thanks!
J
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not be pretty but works for me.
An AIC difference equal or less than 2 is a tie, anything higher is
evidence for the model with the less AIC (Sakamoto et al., Akaike
Information Criterion Statistics, KTK Scientific Publishers, Tokyo).
I wouldn't go quite as far as Frank Harrell did
have 124 variables(mix of categorical and
continuous)
how would i select(R code) attribute - ie. independent variable from those
124 variable(Variable selection) so that i can build a model using glm
pls. give me codes in R- on how to do that
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. Model selection without shrinkage
(penalization) seems to offer benefits but this is largely a mirage.
Frank
Rubén Roa wrote
-Mensaje original-
De: Bert Gunter [mailto:gunter.berton@]
Enviado el: jueves, 26 de enero de 2012 21:20
Para: Rubén Roa
CC: Ben Bolker; Frank Harrell
Ruben you are mistaken on every single point. But I see it's not worth
continuing this discussion.
Frank
Rubén Roa wrote
-Mensaje original-
De: r-help-bounces@ [mailto:r-help-bounces@] En nombre de Frank Harrell
Enviado el: viernes, 27 de enero de 2012 14:28
Para: r-help@
Asunto
the conference that you may also want to
take advantage of.
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?
Any advice, please?
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SD
118.5308396 118.3771115 0.1435944
Z P
1.0705717 0.2843620
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. Is this
how the procedure works in R?
2. Is the reason you recommend repeating k-fold 100 times because the
partitioning is random, ie not 1st 10th, 2nd 10, et cetera so you might
obtain slightly different results?
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- Department of Internal Medicine
University of Virginia, Charlottesville, Virginia
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/nomogram_2.jpeg
Please can I do to have linear predictor between 0 to 1.
Thanks very much for your Help
Komine
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Using anything other than deviance (or likelihood) as the objective function
will result in a suboptimal model.
Frank
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, 2011 at 8:11 AM, Frank Harrell
lt;f.harr...@vanderbilt.edugt; wrote:
Using anything other than deviance (or likelihood) as the objective
function
will result in a suboptimal model.
Frank
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structure. I am wondering which CIs are better.
I guess bootstrapping one, but is it right?
I would appreciate your help in advance.
--
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(11/05/16 12:25), Frank Harrell wrote:
I think you are doing this correctly except for one thing. The
validation
and other inferential calculations
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narrow
down the
variables based on univarate analysis and build a multivariate model from
that.
Many thanks in advance.
...Tao
- Original Message
From: Frank Harrell lt;f.harr...@vanderbilt.edugt;
To: r-help@r-project.org
Sent: Mon, May 16, 2011 11:25:20 AM
Subject: Re
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it.
Thank you,
Ana
On Wed, May 18, 2011 at 3:14 PM, Frank Harrell
lt;f.harr...@vanderbilt.edugt;wrote:
First of all, use the correct terminology for the statistical method.
It is not productive to identify 'significant' genes unless you use quite
complex methods. This kind of endeavor would
to validate an existing model?
Anything different?
Many thanks!
...Tao
- Original Message
From: Frank Harrell lt;f.harr...@vanderbilt.edugt;
To: r-help@r-project.org
Sent: Tue, May 17, 2011 10:51:02 AM
Subject: Re: [R] changes in coxph in survival from older version
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whether this is enough improvement though.
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Kohkichi
(11/05/22 23:27), Frank Harrell wrote:
S.D. is the standard deviation (standard error) of Dxy. It already
includes
the effective sample size in its computation so the sqrt(n) terms is not
needed. The help file for rcorr.cens has
+ mldata$dr0 +
mldata$dr1 + mldata$yr_tch_exp + mldata$yr_tch_exp_s + mldata$ismgdr +
mldata$ismgyr_t_A + mldata$pair)
Error: inherits(object, formula) is not TRUE
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I have not been able to figure out the format for specifying limits, at,
labels in scales - list(relation='free', limits=..., at=..., labels=...)
when there is more than one paneling variable, e.g., xyplot(y ~ x | a*b).
Thanks for any guidance.
Frank
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Thanks very much David and Bert. That did it.
Frank
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of an .Rd file is:
f - ols(y ~ pol(x1,2) + pol(x2,2) + pol(x1,2) %ia% pol(x2,2),
subset=group==g)
Putting \ before the % gets around the problem but I didn't have to do that
before.
Any ideas?
Thanks Frank
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this output
in the first place.
As ever, thanks in advance are likely due to Frank Harrell, without whom
many things would be much more difficult.
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PLEASE do read
.
More details are at http://biostat.mc.vanderbilt.edu/Rrms
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This is not really an R question, and it indicates that you have a good deal
of studying to do about quantile regression before you rely on it.
Frank
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See the contents function in the Hmisc package.
karena wrote:
Is there any function in R which does the same thing as what 'PROC
CONTENTS' does in SAS?
thanks,
karena
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than 6 non
missing observations.
George
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,
xlab='',ylab='')
text(rep(.5,p), 1:p, v, adj=1)
maxabsr - max(abs(r[row(r) != col(r)]))
for(i in 1:p) {
for(j in 1:p) {
if(i = j) next
lines(c(i,i),c(j,j+r[i,j]/maxabsr/2), lwd=3)
lines(c(i-.2,i+.2),c(j,j), col=gray(.7))
}
text(i, i, v[i], srt=-45, adj=0)
}
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I know about the current.row, current.column, and panel.number functions that
are useful within panel functions written for lattice. Are there easy ways
to obtain the names of the conditioning variables (those appearing after |)
and their values for the current panel?
Thanks
Frank
-
Frank
with writing one based on details like thoseyou have elucidated. But
this is really not good programming practice, imo.
Contrary and more informed views welcome.
Cheers,
Bert
On Mon, Jun 20, 2011 at 7:17 AM, David Winsemius
lt;dwinsem...@comcast.netgt; wrote:
Frank Harrell wrote:
I know
.
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.
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-Raffele hospital
Milan, Italy
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is risky.
Frank
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the package much more compact. Thanks for listening. I'm
writing to r-help because this may applied to other R packages as well.
Frank
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I was wrong about this. The dataset is small. Most of the space is taken up
by a nice tutorial on rpart.plot. Still I would favor linking to datasets
rather than duplicating part of them.
Thanks
Frank
Frank Harrell wrote:
I was glad to see the new rpart.plot package by Stephen Milborrow. I
-contained, reproducible code.
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Chris,
I've fixed Surv in rms. The fix will be in the next release. For now you
can do source('http://biostat.mc.vanderbilt.edu/tmp/Surv.s') after issuing
require(rms).
Frank
Frank Harrell wrote
Chris,
Thanks for sending the specifics. It appears that I've let Surv in rms
fall behind
example and do the
calculations by hand.
Frank
blackscorpio81 wrote
Dear R users,
Please allow to me ask for your help.
I am currently using Frank Harrell Jr package rms to model ordinal
logistic regression with proportional odds. In order to assess model
predictive ability, C concordance
,
Please allow to me ask for your help.
I am currently using Frank Harrell Jr package rms to model ordinal
logistic regression with proportional odds. In order to assess model
predictive ability, C concordance index is displayed and equals to
0.963.
This is the code I used with the data attached
For lrm fits, predict(fit, type='mean') predicts the mean Y, not a
probability.
Frank
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Department of Biostatistics, Vanderbilt University
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*RMS Short Course 2013*
Frank E. Harrell, Jr., Ph.D., Professor and Chair
Department of Biostatistics, Vanderbilt University School of Medicine
*March 4, 5 6, 2013*
8:00am - 4:30pm
Student Life Center Board of Trust Room
Vanderbilt University
Nashville Tennessee USA
See
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PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
-
Frank Harrell
Department of Biostatistics, Vanderbilt University
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.
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Frank Harrell
Department of Biostatistics, Vanderbilt University
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/xgsu00/
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PLEASE do read the posting guide
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and provide commented, minimal, self-contained, reproducible code.
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Frank
invocation of model.frame( ) causes R to try to do arithmetic addition to
create a single dependent variable.
Thanks
Frank
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Frank Harrell
Department of Biostatistics, Vanderbilt University
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Thanks for your reply Gabor. That doesn't handle a mixture of factor and
numeric variables on the left hand side.
Frank
Gabor Grothendieck wrote
On Fri, Mar 1, 2013 at 7:16 PM, Frank Harrell lt;
f.harrell@
gt; wrote:
The lattice package uses special logic to allow for multiple
left-hand
@
[mailto:
r-help-bounces@
] On Behalf
Of Frank Harrell
Sent: Friday, March 01, 2013 4:17 PM
To:
r-help@
Subject: [R] Multiple left hand side variables in a formula
The lattice package uses special logic to allow for multiple
left-hand-side
variables in a formula, e.g. y1 + y2 ~ x
Achim this is perfect. I had not seen Formula before. Thanks for writing
it!
Frank
Achim Zeileis-4 wrote
On Fri, 1 Mar 2013, Frank Harrell wrote:
Thank you Bill. A temporary re-arrangement of the formula will allow me
to
do the usual subset= na.action= processing afterwards. Nice idea
, Frank Harrell lt;
f.harrell@
gt; wrote:
The lattice package uses special logic to allow for multiple
left-hand-side
variables in a formula, e.g. y1 + y2 ~ x. Is there an elegant way to
do
this outside of lattice? I'm trying to implement a data summarization
function that logically takes
) :
unimplemented type 'expression' in 'HashTableSetup'
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Frank Harrell
Department of Biostatistics, Vanderbilt University
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Whoops - these 2 lines should have been omitted from the program:
n - sprintf('%s (n%s=%g, n%s=%g)', v, nam[1],n[1], nam[2],n[2])
vn[var == v] - n
Frank Harrell wrote
I would like to have a lattice conditioning ( | var ) variable have
expression() as values because I want panel labels
]]
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mailing list
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PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
-
Frank Harrell
Department of Biostatistics
I'm not sure why you posted the original note. I quit using SAS in 1991 and
haven't needed it yet.
Frank
RogerJDeAngelis wrote
Sorry about the double post. But I keep getting 'post' rejections, so I
resubmitted about an hour later.
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Frank Harrell
Department of Biostatistics
, reproducible code.
-
Frank Harrell
Department of Biostatistics, Vanderbilt University
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