Displaying 20 results from an estimated 40000 matches similar to: "simple list question"
2008 Dec 13
0
simple list question (question withdrawn)
My apology to the list, as it turns out the moment after I hit the send
button, I found that the first element in the list was a null. The error
message reflects that.
> _____________________________________________
> From: Barker, Chris
> Sent: Friday, December 12, 2008 6:30
> To: 'r-help@r-project.org'
> Subject: simple list question
>
>
> I'd
2007 Feb 15
1
bootcov and cph error
Hi all,
I am trying to get bootstrap resampled estimates of covariates in a Cox
model using cph (Design library).
Using the following I get the error:
> ddist2.abr <- datadist(data2.abr)
> options(datadist='ddist2.abr')
> cph1.abr <- cph(Surv(strt3.abr,loc3.abr)~cov.a.abr+cov.b.abr,
data=data2.abr, x=T, y=T)
> boot.cph1 <- bootcov(cph1.abr, B=100, coef.reps=TRUE,
2010 Aug 05
3
How to extract se(coef) from cph?
Hello,
I am modeling some survival data wih cph (Design). I have modeled a predictor
which showed non linear effect with restricted cubic splines. I would like to
retrieve the se(coef) for other, linear, predictors. This is just to make nice
LateX tables automatically. I have the coefficients with coef().
How do I do that?
Thanks,
David Biau.
[[alternative HTML version deleted]]
2009 Feb 17
1
Processing a list of fit objects
Hi, I have a list of fit objects (fit objects from HMISC functions)
I create elements in the list in this way
lrm.sumtot <- lrm( ae7bepn ~ trarm + sumtot , data=sd.fix)
lrm.list[['lrm.sumtot']] <- lrm.sumtot
And I can run (anova(lrm.sumtot))
The following also gives the anova I'd expect
zz <- lrm.list[['lrm.sumtot']];anova(zz)
And similarly for the summary
2001 Sep 18
1
case weights in coxph (survival)
Hi,
I am having trouble with the survival library, particualrily the coxph
function.
the following works
coxph(jtree9$cph.call,z,rep(1,dim(z)[1]))
Call:
coxph(formula = jtree9$cph.call, data = z, weights = rep(1, dim(z)[1]))
coef exp(coef) se(coef) z p
SM 0.2574 1.294 0.0786 3.274 1.1e-03
Sex -0.1283 0.880 0.1809 -0.709
2007 Aug 27
2
validate (package Design): error message "subscript out of bounds"
Dear R users
I use Windows XP, R2.5.1 (I have read the posting guide, I have
contacted the package maintainer first, it is not homework).
In a research project on renal cell carcinoma we want to compute
Harrell's c index, with optimism correction, for a multivariate
Cox regression and also for some univariate Cox models.
For some of these univariate models I have encountered an error
2004 Dec 15
2
using Hmisc and Design library
Hi, I encountered a weird problem when using the
Design and Hmisc problem. I have 2 data frame called
"a" and "b", both have 3 columns: "time", "status" and
"scores", a sample of the data frame is like:
data frame "a":
time status scores
1 21 1 99.61
2 38 0 101.11
3 51 0 100.62
4 48 0 87.52
5 78 0
2004 Apr 21
1
difference between coxph and cph
Hi. I am using Windows version of R 1.8.1. Being somewhat new to survival
analysis, I am trying to compare cph (Design) with coxph (survival) for use
with a survival data set.
I was wondering why cph and coxph provide me with different confidence
intervals
for the hazard ratios for one of the variables. I was wondering if I am
doing something wrong? Or if the two functions are calculating hazard
2007 Aug 06
1
(Censboot, Z-score, Cox) How to use Z-score as the statistic within censboot?
Dear R Help list,
My question is regarding extracting the standard error or Z-score from a
cph or coxph call. My Cox model is: -
modz=cph(Surv(TSURV,STATUS)~RAGE+DAGE+REG_WTIME_M+CLD_ISCH+POLY_VS,
data=kidneyT,method="breslow", x=T, y=T)
I've used names(modz) but can't see anything that will let me extract
the Z scores for each coefficient or the standard errors in the same
2007 Dec 18
1
hazard ratio of interaction Cox model
Dear Forum,
I have a question about interaction estimate in the Cox model:
why the hazard ratio of the interaction is not produced in the summary of the model?
(Instead, the estimate of the coefficient is given in the print of the model.)
# Example:
modINT <-cph( Surv(T_BASE, T_FIN,STATUS)~ NYHA + ASINI + RFP + FE_REC + XX_PR*XX_DISF)
print(modINT)
coef se(coef) z
2000 Aug 07
1
predict.lm is broken in 1.1.0-patched (2000-August-7) (PR#627)
On 7 Aug 2000, Peter Dalgaard BSA wrote:
> ripley@stats.ox.ac.uk writes:
>
> > predict.lm has been broken by recent changes to the patched branch.
> >
> > It fails for all singular fits. An example:
<snip>
> Sometimes the fix for one bug uncovers another. We have
>
> > coef.aov
> function (object, ...)
> {
> z <- object$coef
>
2011 Feb 21
2
Interpreting the example given by Prof Frank Harrell in {Design} validate.cph
Dear R-help,
I am having a problem with the interpretation of result from validate.cph in
the Design package.
My purpose is to fit a cox model and validate the Somer's Dxy. I used the
hypothetical data given in the help manual with modification to the cox
model fit. My research problem is very similar to this example.
This is the model without stratification:
> library(Design)
> f1
2015 Feb 04
2
Interpretación de coeficientes en un cox proportional hazards con variable strata
Buenas.
Abajo pongo la salida de un modelo de cox , dónde he estratificado por
una variable de país (Countryb) y por otra (Q6). Además hay interacción
entre la variable mobilityPDurG2 (es una variable 0,1, y 0 es la
categoría de referencia) país.
La categoría de referencia para país es "united kingdom".
Mi duda surge si quiero calcular el hazard ratio para los que tienen un
1
2005 Mar 15
2
Lemon drops
I bumped into the following situation:
Browse[1]> coef
deg0NA deg4NA deg8NA deg0NP deg4NP deg8NP
(Intercept) 462 510 528 492 660 762
Browse[1]> coef[,1]
[1] 462
Browse[1]> coef[,1,drop=F]
deg0NA
(Intercept) 462
where I really wanted neither, but
(Intercept)
462
Anyone happen to know a neat way out of the conundrum?
I can think of
2013 Jul 06
1
problem with BootCV for coxph in pec after feature selection with glmnet (lasso)
Hi,
I am attempting to evaluate the prediction error of a coxph model that was
built after feature selection with glmnet.
In the preprocessing stage I used na.omit (dataset) to remove NAs.
I reconstructed all my factor variables into binary variables with dummies
(using model.matrix)
I then used glmnet lasso to fit a cox model and select the best performing
features.
Then I fit a coxph model
2010 Sep 29
1
Trying to avoid loop structure
Dear R-helpers,
I'm trying to associate linear coefficients (intercept and slope) to tens of thousands of observations based on a table with benchmark values.
#####Example - Value table and their corresponding coefficients (intercept and slope)
coef = data.frame(cbind(st=c(1:5),b = runif(5,0.3,5),a = seq(0.5,5,1)))print(coef)
#Example of observations to be computedobs = runif(20,1,5)print(obs)
2004 Dec 29
1
Discrepancy between intervals.lme and coef.lme
I'm using R on Windows v2.0.1 with the nlme package (v3.1-53) and am finding some unexpected discrepancies in the output of intervals.lme and coef.lme. I've included a toy dataset at the end, but briefly, the data are longitudinal data from couples in marital therapy. Each spouse's relationship satisfaction is measured 4 times; I've fit both linear and quadratic models to the
2009 Sep 26
1
Multiple comparisons for coxph survival analysis model
Hello, all R-users!
I am working on fitting a survival analysis model using the coxph
function for Cox proportional hazards regression model. Data look like
usual:
==========================
group block death censor
Group1 1 4 1
Group1 1 12 1
...
Group2 30 4 1
Group2 30 4 1
...
Group3 57 16
2009 Mar 10
2
simple question beginner
Hi there,
I am beginner in R and I have some basic question. Suppose I run a common procedure such as a t test or cox model like below:
out<-coxph( Surv(tstart,tstop, death1) ~ x1+x1:log(tstop+1) , test1,method=c("breslow"))
Which yields the following result:
Call:
coxph(formula = Surv(tstart, tstop, death1) ~ x1 + x1:log(tstop +
1), data = test1, method =
2002 Feb 27
1
Bug in glm.fit? (PR#1331)
G'day all,
I had a look at the GLM code of R (1.4.1) and I believe that there are
problems with the function "glm.fit" that may bite in rare
circumstances. Note, I have no data set with which I ran into
trouble. This report is solely based on having a look at the code.
Below I append a listing of the glm.fit function as produced by my
system. I have added line numbers so that I