Displaying 20 results from an estimated 100 matches similar to: "survest() for cph() in Design package"
2009 Apr 14
1
Function call error in cph/survest (package Design)
Dear UseR,
I do not know if this a problem with me, my data or cph/survest in package
design. The example below works with a standard data set, but not with my
data, but I cannot locate the problem.
Note that I am using an older package of survival to avoid a problem with
the newly renamed function in survival meeting Design.
Dieter
# First, check standard example to make sure
library(Design)
2007 Nov 21
0
survest and survfit.coxph returned different confidence intervals on estimation of survival probability at 5 year
I wonder if anyone know why survest (a function in Design package) and
standard survfit.coxph (survival) returned different confidence
intervals on survival probability estimation (say 5 year).
I am trying to estimate the 5-year survival probability on a continuous
predictor (e.g. Age in this case). Here is what I did based on an
example in "help cph". The 95% confidence intervals
2009 Mar 26
2
R 2.8.1 and 2.9 alpha crash when running survest of Design package
Dear Prof Harrell and everyone,
My PC: Window XP service pack 3 and service pack 2
R version 2.8.1 and 2.9 alpha
For the last 3 days, after updating R, my two computers have been facing
problems when running existing and runable R commands that involves with
Design package
I attempt to use 'survest', but I failed all the times with R (both 2.8.1
and 2.9 alpha) being shut down
2010 Jul 07
3
Boxplots over a Scatterplot
Hello-
I'm new to R, coding and stats. (Oh no.)
Anyway, I have about 12000 data points in a data.frame (dealing with
dimensions and geological stage information for fossil protists) and have
plotted them in a basic scatter plot. I also added a boxplot to overlay
these points. Each worked fine independently, but when I attempt to
superimpose them with add=true, I get a different scale for
2010 May 05
2
[LLVMdev] Why llvm function name is different with . and ..
declare i8 @llvm.atomic.load.max.i8.p0i8( i8* <ptr>, i8 <delta> )
declare i16 @llvm.atomic.load.max.i16.p0i16( i16* <ptr>, i16 <delta> )
declare i32 @llvm.atomic.load.max.i32.p0i32( i32* <ptr>, i32 <delta> )
declare i64 @llvm.atomic.load.max.i64.p0i64( i64* <ptr>, i64 <delta> )
declare i8 @llvm.atomic.load.min.i8.p0i8( i8* <ptr>, i8
2010 May 05
0
[LLVMdev] Why llvm function name is different with . and ..
Its seems an bug in langref, is there anyone have an look or give an explain?
2010/5/5, 罗勇刚(Yonggang Luo) <luoyonggang at gmail.com>:
> declare i8 @llvm.atomic.load.max.i8.p0i8( i8* <ptr>, i8 <delta> )
> declare i16 @llvm.atomic.load.max.i16.p0i16( i16* <ptr>, i16 <delta> )
> declare i32 @llvm.atomic.load.max.i32.p0i32( i32* <ptr>, i32
2009 Oct 26
1
Unable to get Legend with survplot rms package
Hello,
I apologize for the post as I am certainly overlooking a simple
solution to my difficulties with getting a legend to print on a
survplot from the rms package.
I am plotting the following:
survplot(survest(fita), n.risk=T, conf='none', cex.n.risk=.85, dots=T,
col='gray10', lty=2)
survplot(survest(fit), n.risk=F, conf='none', add=T)
survplot(survest(fitb), n.risk=F,
2009 May 20
1
turning off specific types of warnings
Dear R users,
I have a long function that among other things uses the "survest" function from the Design package. This function generates the warning:
In survest.cph (...)
S.E. and confidence intervals are approximate except at predictor means.
Use cph(...,x=T,y=T) (and don't use linear.predictors=) for better estimates.
I would like to turn this specific warning off, as it
2009 Feb 18
1
Age as time-scale in a cox model-How to calculate x-time risk?
Dear R users,
My question is more methodology related rather than specific to R usage. Using time on study as time in a cox model, eg:
library(Design)
stanf.cph1=cph(Surv(time, status) ~ t5+id+age, data=stanford2, surv=T)
#In this case the 1000-day survival probability would be:
stanf.surv1=survest(stanf.cph1, times=1000)
#Age in this case is a covariate.
#I now want to compare the above
2016 Nov 04
0
Major Update to rms package: 5.0-0
A major new version of the rms package is now on CRAN. The most
user-visible changes are:
- interactive plotly graphic methods for model fits. The best example of
this is survplot for npsurv (Kaplan-Meier) estimates where the number of
risk pop up as you hover over the curves, and you can click to bring up
confidence bands for differences in survival curves
- html methods for model fit
2016 Nov 04
0
Major Update to rms package: 5.0-0
A major new version of the rms package is now on CRAN. The most
user-visible changes are:
- interactive plotly graphic methods for model fits. The best example of
this is survplot for npsurv (Kaplan-Meier) estimates where the number of
risk pop up as you hover over the curves, and you can click to bring up
confidence bands for differences in survival curves
- html methods for model fit
2011 Aug 04
2
survival probability estimate method
Hi, I was reading a paper published in JCO "Prediction of risk of distant recurrence using 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study" (ICO 2010 28: 1829). The author uses a method to estimate the 9-year risk of distant recurrence as a function of continuous recurrence
2006 Jun 15
0
survival probabilities with cph (counting process)
Hi,
I have fitted a cox model with time-varying covariates (counting process style)
using the cph function of the Design package. Now I want to know the survival probabilities at each time point given the history of a single individual.
I know the survest function, but I am not sure how to interpretet its output when using time-varying covariates. Does it just give the probabilities as if it
2011 Mar 01
0
Major update to rms package
A new version of rms is now available on CRAN for Linux and Windows (Mac
will probably be available very soon). Largest changes include latex
methods for validate.* and adding the capability to force a subset of
variables to be included in all backwards stepdown models (single model or
validation by resampling).
Recent updates:
* In survplot.rms, fixed bug (curves were undefined if
2011 Mar 01
0
Major update to rms package
A new version of rms is now available on CRAN for Linux and Windows (Mac
will probably be available very soon). Largest changes include latex
methods for validate.* and adding the capability to force a subset of
variables to be included in all backwards stepdown models (single model or
validation by resampling).
Recent updates:
* In survplot.rms, fixed bug (curves were undefined if
2009 Feb 16
1
How do i compute predicted failure time from a cox model?
Given a cox model:
library(Hmisc); library(survival); (library(Design);
cox.model=cph(Surv(futime, fustat) ~ age, data=ovarian, surv=T)
str(cox.model)
What I need is the total estimated time until failure (death), not the
probability of failing at a given time (survival probability), or hazard
etc, which is what I get from survest and predict for example.
I suspect the answer is
2004 Nov 03
3
Estimating survival?
Hi,
Sorry to trouble the list. I have a problem which I'm not sure how to resolve.
I have a Cox model with 1 independent variable with 2 categories (and
thus 2 survival curves on plotting survfit)
How can I get an estimate of survival for each category at a
particular time point, with standard error?
Looking through ?cph and ?coxph, I'm not quite sure how to go about
that. I would
2003 Apr 24
1
"Missing links": Hmisc and Design docs
Hi folks,
Using R Version 1.6.2 (2003-01-10)
on SuSE Linux 7.2,
I just installed Hmisc_1.5-3.tar.gz and Design_1.1-5.tar.gz
These were taken from
http://hesweb1.med.virginia.edu/biostat/s/library/r
Checked the dependencies:
Hmisc: grid, lattice, mva, acepack -- all already installed
Design: Hmisc, survival -- survival already installed, so
installed Hmisc first
All seems to go
2010 May 26
3
Problem with plotting survival predictions from cph model
Dear R-helpers,
I am working with 'cph' models from 'rms' library. When I build simple
survival models, based on 'Surv(time, event)', everything is fine and I
can make nice plots using plot(Predict(f, time=3)).
However, recently I tried to be more specific and used 'Surv(start,
stop, event)' type model. Using this model 'plot(Predict(f))' works OK,
but
2019 Sep 18
2
Vectorizing multiple exit loops
On 9/17/2019 3:17 AM, Renato Golin wrote:
> Hi Philip,
>
> Apologies for leaving this thread linger so long. It was in my
> back-burner but Alex's weekly remind me to reply (thanks again,
> Alex!). Starting from the end...
>
> On Mon, 9 Sep 2019 at 18:53, Philip Reames via llvm-dev
> <llvm-dev at lists.llvm.org> wrote:
>> Current Plans
>>
>> At