Displaying 20 results from an estimated 10000 matches similar to: "Survreg/psm output"
2007 Jun 18
1
psm/survreg coefficient values ?
I am using psm to model some parametric survival data, the data is for
length of stay in an emergency department. There are several ways a
patient's stay in the emergency department can end (discharge, admit, etc..)
so I am looking at modeling the effects of several covariates on the various
outcomes. Initially I am trying to fit a survival model for each type of
outcome using the psm
2005 Aug 27
1
survival parametric question
Hi to all,
I am working on design package using survival function.
First using PSM and adopting a weibull specification for the baseline hazard , I have got the following results(since weibull has both PH and AFT propreties ,in addition I have used the PPHSm command):
Value Std. Error z p
(Intercept) 1.768 1.0007 1.77 7.73e-02
SIZE -0.707 0.0895 -7.90 2.80e-15
2004 Nov 23
6
Weibull survival regression
Dear R users,
Please can you help me with a relatively straightforward problem that I
am struggling with? I am simply trying to plot a baseline survivor and
hazard function for a simple data set of lung cancer survival where
`futime' is follow up time in months and status is 1=dead and 0=alive.
Using the survival package:
lung.wbs <- survreg( Surv(futime, status)~ 1, data=lung,
2010 Nov 15
1
interpretation of coefficients in survreg AND obtaining the hazard function
1. The weibull is the only distribution that can be written in both a
proportional hazazrds for and an accelerated failure time form. Survreg
uses the latter.
In an ACF model, we model the time to failure. Positive coefficients
are good (longer time to death).
In a PH model, we model the death rate. Positive coefficients are
bad (higher death rate).
You are not the first to be confused
2004 Feb 02
1
PSM function in Design package (PR#6525)
Full_Name: Oleg Raisky
Version: 1.8.1
OS: Windows 2000
Submission from: (NULL) (63.246.203.107)
This is a completely fresh R install. I'm trying to use Design package. Every
time I run the first example for psm() I'm getting an error <<couldn't find
function "survreg.fit">>. However, survreg.fit does exists in the search path.
Is there something I can do to fix
2005 Jan 20
2
(no subject)
Hello
I would like to compare the results obtained with a classical non
parametric proportionnal hazard model with a parametric proportionnal
hazard model using a Weibull.
How can we obtain the equivalence of the parameters using coxph(non
parametric model) and survreg(parametric model) ?
Thanks
Virginie
2006 Jul 07
6
parametric proportional hazard regression
Dear all,
I am trying to find a suitable R-function for
parametric proportional hazard regressions. The
package survival contains the coxph() function which
performs a Cox regression which leaves the base hazard
unspecified, i.e. it is a semi-parametric method. The
package Design contains the function pphsm() which is
good for parametric proportional hazard regressions
when the underlying base
2010 Nov 16
1
Re : interpretation of coefficients in survreg AND obtaining the hazard function for an individual given a set of predictors
Thanks for sharing the questions and responses!
Is it possible to appreciate how much the coefficients matter in one
or the other model?
Say, using Biau's example, using coxph, as.factor(grade2 ==
"high")TRUE gives hazard ratio 1.27 (rounded).
As clinician I can grasp this HR as 27% relative increase. I can
relate with other published results.
With survreg the Weibull model gives a
2010 Nov 13
2
interpretation of coefficients in survreg AND obtaining the hazard function for an individual given a set of predictors
Dear R help list,
I am modeling some survival data with coxph and survreg (dist='weibull') using
package survival. I have 2 problems:
1) I do not understand how to interpret the regression coefficients in the
survreg output and it is not clear, for me, from ?survreg.objects how to.
Here is an example of the codes that points out my problem:
- data is stc1
- the factor is dichotomous
2013 Jan 14
1
Does psm::Surv handle interval2 data?
Does Surv in psm handle interval2 data? The argument list seems to indicate it does but I get an error.
Thanks,
Chris
# code
library('survival')
left <- c(1, 3, 5, NA)
right <-c(2, 3, NA, 4)
Surv(left, right, type='interval2')
survreg(Surv(left, right, type='interval2') ~ 1)
library('rms')
Surv(left, right, type='interval2') # error
args(Surv)
2005 Feb 24
2
survreg with gamma distribution: re-post
Dear r-help subscribers,
A couple of weeks ago I sent the following message to the r-help mail
list. It hasn't generated any response, and I could really use some help
on this. Anyone able to help?
Thanks again,
Roger Dungan
>>
I am working on some survival analysis of some interval censored failure
time data in R. I have done similar analysis before using PROC LIFEREG
in SAS. In
2008 Aug 26
1
Variance-covariance matrix
Dear R help forum,
I am using the function 'coxph' to obtain hazard ratios for the comparison
of a standard treatment to new treatments. This is easily obtained by
fitting the relevant model and then calling exp(coef(fit1)) say.
I now want to obtain the hazard ratio for the comparison of two non-standard
treatments.
>From a statistical point of view, this can be achieved by dividing
2009 Jun 07
1
Survreg function for loglogistic hazard estimation
I am trying to use R to do loglogistic hazard estimation. My plan is to
generate a loglogistic hazard sample data and then use survreg to estimate
it. If everything is correct, survreg should return the parameters I have
used to generate the sample data.
I have written the following code to do a time invariant hazard estimation.
The output of summary(modloglog) shows the factor loading of
2009 Jun 09
2
Isolating a single plot from plots produced simultaneously
Dear R-Help,
I am using the 'mfp' package. It produces three plots (as I am using
the Cox model) simultaneously which can be viewed together using the
following code:
fit <- mfp(Surv(rem.Remtime,rem.Rcens)~fp(age)+strata(rpa),family=cox,data=nearma,select=0.05,verbose=TRUE)
par(mfrow=c(2,2))
plot(fit)
They can be viewed separately but the return key must be pressed after
each graph
2012 Apr 22
1
Survreg
Hi all,
I am trying to run Weibull PH model in R.
Assume in the data set I have x1 a continuous variable and x2 a
categorical variable with two classes (0= sick and 1= healthy). I fit the
model in the following way.
Test=survreg(Surv(time,cens)~ x1+x2,dist="weibull")
My questions are
1. Is it Weibull PH model or Weibull AFT model?
Call:
survreg(formula = Surv(time, delta) ~ x1
2008 Sep 29
1
Hazard plot
Hi All,
This sounds a relatively simple query, and I hope it is!
I am looking at a continuous variable, age. I am looking at time to
12-month remission and can calculate the HR and 95% confidence interval are
follows:
coxfita = coxph(Surv(rem.Remtime,rem.Rcens)~nearma$all.age,data=nearma)
exp(coxfita$coefficients)
exp(confint(coxfita))
However, because I am looking at age as a continuous
2010 May 25
2
Relative Risk/Hazard Ratio plots for continuous variables
Dear all,
I am using Windows and R 2.9.2 for my analyses. I have a large dataset and
I am particularly interested in looking at time to an event for a continuous
variable. I would like to produce a plot of log(relative risk) or relative
risk (also known as hazard ratio) against the continuous variable.
I have spent a long time looking for advice on how to do this but my search
has proved
2009 Dec 16
1
Baseline survival estimate
Dear R-help,
I am trying to obtain the baseline survival estimate of a fitted Cox model
(S_0 (t)). I know that previous posts have said use 'basehaz' but this
gives the baseline hazard function and not the baseline survival estimate.
Is there a way to obtain the baseline survival estimate or do I have to use
the formula which does something like S(t) = exp[- the integral from 0 to t
of
2008 Jan 23
2
Parametric survival models with left truncated, right censored data
Dear All,
I would like to fit some parametric survival models using left
truncated, right censored data in R. However I am having problems
finding a function to fit parametric survival models which can handle
left truncated data.
I have tested both the survreg function in package survival:
fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1)
and the psm function in package
2010 May 05
1
Error messages with psm and not cph in Hmisc
While
sm4.6ll<-fit.mult.impute(Surv(agesi, si)~partner+ in.love+ pubty+ FPA+
strat(gender),fitter = cph, xtrans = dated.sexrisk2.i, data =
dated.sexrisk2, x=T,y=T,surv=T, time.inc=16)
runs perfectly using Hmisc, Design and mice under R11 run via Sciviews-K,
with
library(Design)
library(mice)
ds2d<-datadist(dated.sexrisk2)
options(datadist="ds2d")