Displaying 20 results from an estimated 1000 matches similar to: "Survreg object"
2009 Nov 13
2
survreg function in survival package
Hi,
Is it normal to get intercept in the list of covariates in the output of survreg function with standard error, z, p.value etc? Does it mean that intercept was fitted with the covariates? Does Value column represent coefficients or some thing else?
Regards,
-------------------------------------------------
tmp = survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian,
2003 Feb 27
2
interval-censored data in survreg()
I am trying to fit a lognormal distribution on interval-censored
data. Some of my intervals have a lower bound of zero.
Unfortunately, it seems like survreg() cannot deal with lower
bounds of zero, despite the fact that plnorm(0)==0 and
pnorm(-Inf)==0 are well defined. Below is a short example to
reproduce the problem.
Does anyone know why survreg() must behave that way?
Is there an alternate
2006 Apr 25
5
Heteroskedasticity in Tobit models
Hello,
I've had no luck finding an R package that has the ability to estimate a
Tobit model allowing for heteroskedasticity (multiplicative, for example).
Am I missing something in survReg? Is there another package that I'm
unaware of? Is there an add-on package that will test for
heteroskedasticity?
Thanks for your help.
Cheers,
Alan Spearot
--
Alan Spearot
Department of Economics
2008 Jul 02
1
survival package test stats
Hello,
Is there a function in the survival package that will allow me to test a subset of independent variables for joint significance? I am thinking along the lines of a Wald, likelihood ratio, or F-test. I am using the survreg procedure to estimate my parameters. Thank you.
Geoff
Geoffrey Smith
Visiting Assistant Professor
Department of Finance
University of Illinois at Urbana-Champaign
2008 Mar 03
1
Problem plotting curve on survival curve
Calum had a long question about drawing survival curves after fitting a Weibull
model, using pweibull, which I have not reproduced.
It is easier to get survival curves using the predict function. Here is a
simple example:
> library(survival)
> tfit <- survreg(Surv(time, status) ~ factor(ph.ecog), data=lung)
> table(lung$ph.ecog)
0 1 2 3 <NA>
63 113 50 1
2009 Oct 02
1
Weibull survival regression model with different shape parameters
Dear R users,
I'm trying to fit a parametric survival model using the survreg function
with a Weibull distribution.
I'm studying the time to death of individuals from different families
and I would like to fit different shape parameters (ie 1/scale in R) for
each of the families. I looked it up in the help pdf and on the
internet, but I couldn't find anything.
Would it be possible to
2005 May 03
2
comparing lm(), survreg( ... , dist="gaussian") and survreg( ... , dist="lognormal")
Dear R-Helpers:
I have tried everything I can think of and hope not to appear too foolish
when my error is pointed out to me.
I have some real data (18 points) that look linear on a log-log plot so I
used them for a comparison of lm() and survreg. There are no suspensions.
survreg.df <- data.frame(Cycles=c(2009000, 577000, 145000, 376000, 37000,
979000, 17420000, 71065000, 46397000,
2011 Sep 20
0
Using method = "aic" with pspline & survreg (survival library)
Hi everybody. I'm trying to fit a weibull survival model with a spline
basis for the predictor, using the survival library. I've noticed that it
doesn't seem to be possible to use the aic method to choose the degrees of
freedom for the spline basis in a parametric regression (although it's
fine with the cox model, or if the degrees of freedom are specified directly
by the user),
2009 Mar 08
2
survreg help in R
Hey all,
I am trying to use the survreg function in R to estimate the mean and
standard deviation to come up with the MLE of alpha and lambda for the
weibull distribution. I am doing the following:
times<-c(10,13,18,19,23,30,36,38,54,56,59,75,93,97,104,107,107,107)
censor<-c(1,0,0,1,0,1,1,0,0,0,1,1,1,1,0,1,0,0)
survreg(Surv(times,censor),dist='weibull')
and I get the following
2013 Jan 17
3
coxph with smooth survival
Hello users,
I would like to obtain a survival curve from a Cox model that is smooth and does not have zero differences due to no events for those particular days.
I have:
> sum((diff(surv))==0)
[1] 18
So you can see 18 days where the survival curve did not drop due to no events.
Is there a way to ask survfit to fit a nice spline for the survival??
Note: I tried survreg and it did not
2012 Nov 15
2
survreg & gompertz
Hi all,
Sorry if this has been answered already, but I couldn't find it in the
archives or general internet.
Is it possible to implement the gompertz distribution as
survreg.distribution to use with survreg of the survival library?
I haven't found anything and recent attempts from my side weren't
succefull so far.
I know that other packages like 'eha' and
2008 Apr 25
3
Use of survreg.distributions
Dear R-user:
I am using survreg(Surv()) for fitting a Tobit model of left-censored longitudinal data. For logarithmic transformation of y data, I am trying use survreg.distributions in the following way:
tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist="gaussian", data=y.data, scale=0, weights=w)
my.gaussian<-survreg.distributions$gaussian
2011 Jan 10
4
Meaning of pterms in survreg object?
I am trying to model survival data with a Weibull distribution
using survreg. Units are clustered two apiece, sometimes receiving
the same treatment and sometimes opposing treatment.
2010 Nov 25
2
aftreg vs survreg loglogistic aft model (different intercept term)
Hi, I'm estimating a loglogistic aft (accelerated failure time) model, just a
simple plain vanilla one (without time dependent covariates), I'm comparing
the results that I obtain between aftreg (eha package) and survreg(surv
package). If I don't use any covariate the results are identical , if I add
covariates all the coefficients are the same until a precision of 10^4 or
10^-5 except
2005 Apr 26
1
survreg with numerical covariates
Does anyone know if the survreg function in the survival package can fit
numerical covariates ?
When I fit a survival model of the form
survreg( Surv(time,censored) ~ x )
then x is always treated as a factor even if it is numeric (and even if
I try to force it to be numeric using as.numeric(x). Thus, in the
particular example I am analysing, a simple numerical covariate becomes
a factor
2004 May 24
1
bug in extractAIC.survreg (PR#6910)
Full_Name: Dave Ramsey
Version: 1.8.0
OS: win2000
Submission from: (NULL) (202.27.240.6)
there is a bug in extractAIC.survreg in library MASS.
A survreg model object has no component called "residuals". Hence
n <- length(fit$residuals)
returns 0 resulting in errors
workaround: replace
n <- length(fit$residuals)
with
n <- length(residuals(fit))
### sorry: error
2006 Feb 13
2
Survreg(), Surv() and interval-censored data
Can survreg() handle interval-censored data like the documentation
says? I ask because the command:
survreg(Surv(start, stop, event) ~ 1, data = heart)
fails with the error message
Invalid survival type
yet the documentation for Surv() states:
"Presently, the only methods allowing interval censored data are
the parametric models computed by 'survreg'"
2008 Apr 17
1
survreg() with frailty
Dear R-users,
I have noticed small discrepencies in the reported estimate of the
variance of the frailty by the print method for survreg() and the
'theta' component included in the object fit:
# Examples in R-2.6.2 for Windows
library(survival) # version 2.34-1 (2008-03-31)
# discrepancy
fit1 <- survreg(Surv(time, status) ~ rx + frailty(litter), rats)
fit1
fit1$history[[1]]$theta
2007 Jul 11
2
p-value from survreg(), library(survival)
dear r experts:
It seems my message got spam filtered, another try:
i would appreciate advice on how to get the p-value from the object 'sr'
created with the function survreg() as given below.
vlad
sr<-survreg(s~groups, dist="gaussian")
Coefficients:
(Intercept) groups
-0.02138485 0.03868351
Scale= 0.01789372
Loglik(model)= 31.1 Loglik(intercept only)= 25.4
2005 Nov 18
1
Truncated observations in survreg
Dear R-list
I have been trying to make survreg fit a normal regression model with left
truncated data, but unfortunately I am not able to figure out how to do it.
The following survreg-call seems to work just fine when the observations are
right censored:
library(survival)
n<-100000
#censored observations
x<-rnorm(n)
y<-rnorm(n,mean=x)
d<-data.frame(x,y)
d$ym<-pmin(y,0.5)