Displaying 20 results from an estimated 10000 matches similar to: "Proportional Hazard Function and Competing risks"
2006 Jul 11
1
Coxph
Dear all,
My question is:
In the Surv object you have two arguments, "time" and "event". I have
two events, namely withdrawn and success.
I use no event or status argument in "Surv" because all my objects "die"
in my data set.
Does coxph function calculate the coefficients correctly when you put no
"event" argument into the Surv object?
2009 Feb 24
0
help: calculations for causespecific hazard ratios in a competing risks analysis with timedependent covariates
Dear R users:
Analysis of the impact of a time-dependent covariate (GVHD or use of steroid after bone marrow transplantation) on two competing endpoints (invasive fungal infection and death) is frequently encountered in the setting of BMT data. Coxph package can be used as the following:
for the analysis of GVHD:
> gvhd -> coxph(Surv(start,stop,status = =1) ~ GVHD, data=bmt.data)
2009 Mar 25
2
Competing risks Kalbfleisch & Prentice method
Dear R users
I would like to calculate the Cumulative incidence for an event
adjusting for competing risks and adjusting for covariates. One way to
do this in R is to use the cmprsk package, function crr. This uses the
Fine & Gray regression model. However, a simpler and more classical
approach would be to implement the Kalbfleisch & Prentice method (1980,
p 169), where one fits cause
2018 Mar 21
1
selectFGR vs weighted coxph for internal validation and calibration curve- competing risks model
Dear Geskus,
I want to develop a prediction model. I followed your paper and analysed thro' weighted coxph approach. I can develop nomogram based on the final model also. But I do not know how to do internal validation of the model and subsequently obtain calibration plot. Is it possible to use Wolbers et al Epid 2009 approach 9 (R code for internal validation and calibration) . It is
2005 Jun 09
1
Prediction in Cox Proportional-Hazard Regression
He,
I used the "coxph" function, with four covariates.
Let's say something like that
> model.1 <- coxph(Surv(Time,Event)~X1+X2+X3+X4,data=DATA)
So I obtain the 4 coefficients B1,B2,B3,B4 such that
h(t) = h0(t) exp(B1*X1+ B2*X2 + B3*X3 + B4*X4).
When I use the function on the same data
> predict.coxph(model.1,type="lp")
how it works in making the prediction?
2009 May 04
1
Nelson-Aalen estimator of cumulative hazard
Hi,
I am computing the Nelson-Aalen (NA) estimate of baseline cumulative hazard in two different ways using the "survival" package. I am expecting that they should be identical. However, they are not. Their difference is a monotonically increasing with time. This difference is probably not large to make any impact in the application, but is annoyingly non-trivial for me to just
2001 Dec 21
1
proportional hazard with parametric baseline function: can it be estimated in R
Greetings --
I would like to estimate a proportional hazard model with a weibull or
lognormal baseline. I have looked at both the coxph() and survreg()
functions and neither appear (to me ) to do it. Am I missing something in
the docs or is there another terrific package out there that will do this.
Many Thanks.
Carl Mason
2006 Apr 03
2
testing proportional hazard in a Cox model including a time-varying covariate
I am using a syntax like coxph(Surv(start, stop, event) ~ X, data) to estimate the effect of X, which may change at each measurement (every 6 months). Is there anyone who knows a way to test the proportional hazard assumption in that case?
Thank you in advance
Jean-François Boudreau
Sherbrooke University
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2011 Dec 10
2
p-value for hazard ratio in Cox proportional hazards regression?
Hi,
I'm new to R and using it for Cox survival analysis. Thanks to this great forum I learned how to compute the HR with its confidence interval.
My question would be: Is there any way to get the p-value for a hazard ratio in addition to the confidence interval?
Thanks,
Thierry
--
Thierry Panje Visiting Student Researcher
Department of Psychology Stanford
2012 Jul 12
1
Cox proportional hazard model and coefficients
Hi,
Here is the summary-output of the Coxph-model I used (the output is based on
the best final model i.e. all significant explanatory variables and their
interactions are included):
coxph(formula = Y ~ LT + Food + Temp2 + LT:Food + LT:Temp2 +
Food:Temp2 + LT:Food:Temp2)
n= 555
coef exp(coef)
se(coef) z
2012 Feb 20
1
Reporting Kaplan-Meier / Cox-Proportional Hazard Standard Error, km.coxph.plot, survfit.object
What is the best way to report the standard error when publishing
Kaplan-Meier plots? In my field (Vascular Surgery), practitioners
loosely refer to the "10% error" cutoff as the point at which to stop
drawing the KM curve. I am interpreting this as the *standard error
of the cumulative hazard*, although I'm having a difficult time
finding some guidelines about this (perhaps I am
2010 Nov 24
2
Is there an equivalent to predict(..., type="linear") of a Proportional hazard model for a Cox model instead?
Hi all,
Is there an equivalent to predict(...,type="linear") of a Proportional hazard
model for a Cox model instead?
For example, the Figure 13.12 in MASS (p384) is produced by:
(aids.ps <- survreg(Surv(survtime + 0.9, status) ~ state + T.categ +
pspline(age, df=6), data = Aidsp))
zz <- predict(aids.ps, data.frame(state = factor(rep("NSW", 83), levels =
2010 Mar 30
5
Problem comparing hazard ratios
Dear R-Helpers,
I am a novice in survival analysis. I have the following code:
for (i in 3:12) print(coxph(Surv(time, status)~a[,i], data=a))
I used it to fit the Cox Proportional Hazard models separately for every
available parameter (columns 3:12) in my data set - with intention to
compare the Hazard Ratios.
However, some of my variables are in range 0.1 to 1.6, others in range
5000 to
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
2009 May 05
3
Cox Proportional Hazard with missing covariate data
Dear friends,
I have used R for some time now and have a tricky question about the coxph-function: To sum it up, I am not sure whether I can use coxph in conjunction with missing covariate data in a model with time-variant covariates. The point is: I know how "old" every piece that I oberserve is, but do not have fully historical information about the corresponding covariates. Maybe you
2011 Nov 20
1
Cox proportional hazards confidence intervals
I am calculating cox propotional hazards models with the coxph
function from the survival package. My data relates to failure of
various types of endovascular interventions. I can successfully
obtain the LR, Wald, and Score test p-values from the coxph.object, as
well as the hazard ratio as follows:
formula.obj = Surv(days, status) ~ type
coxph.model = coxph(formula.obj, df)
fit =
2007 May 17
1
Stratified Cox proportional Hazard Model
Hello everyone,
I am a new user of R. Does anybody know how hazard ratios are extracted
for each factor level in a stratified Cox proportional hazard
regression model? I have a cancer data set where the variable
?differentiation? is a factor with three levels: poor, intermediate and
good. I would like to extract the hazard ratio for each grade level and
relate it to another prognostic factor.
2009 Feb 27
2
Competing risks adjusted for covariates
Dear R-users
Has anybody implemented a function/package that will compute an individual's risk of an event in the presence of competing risks, adjusted for the individual's covariates?
The only thing that seems to come close is the cuminc function from cmprsk package, but I would like to adjust for more than one covariate (it allows you to stratify by a single grouping vector).
Any
2011 Jun 24
1
Competing-risks nomogram
Hi R users,
I'd like to draw a nomogram using a competing-risks regression (crr function
in R), rather than a cox regression. However, the nomogram function provided
in the Design package is not good for this purpose.
Do you have any suggestion.
I really appreciate your help
Many thanks
F.Abdollah, MD
San-Raffele hospital
Milan, Italy
--
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2009 Aug 02
1
Competing Risks Regression with qualitative predictor with more than 2 categories
Hello,
I have a question regarding competing risk regression using cmprsk package (function crr()). I am using R2.9.1. How can I do to assess the effect of qualitative predictor (gg) with more than two categories (a,b,c) categorie c is the reference category. See above results, gg is considered like a ordered predictor !
Thank you for your help
Jan
> # simulated data to test
> set.seed(10)