search for: competently

Displaying 20 results from an estimated 1643 matches for "competently".

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2013 Mar 07
1
Comparing Cox model with Competing Risk model
I have a competing risk data where a patient may die from either AIDS or Cancer. I want to compare the cox model for each of the event of interest with a competing risk model. In the competing risk model the cumulative incidence function is used directly. I used the jackknife (pseudovalue) of the cumulative incidence function for each cause (AIDS or Cancer) in a generalized estimating equation. I
2012 Feb 28
1
Packages/functions for competing risk analysis
Hi Rs, I am analyzing a time to event dataset with several competing risks. 0 = Active by end of study 1 = Stopped treatment to start another treatment 2 = Lost 3 = Dead My event of interest in Lost to Followup but starting a different treatment and dying are competing risks. All 1,2,3 events are events of exiting the study, but it's only 2-LTFU that we are concerned with (I know I am
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
2007 May 25
0
Competing Risks Analysis
I am working on a competing risks problem, specifically an analysis of cause-specific mortality. I am familiar with the cmprsk package and have used it before to create cumulative incidence plots. I also came across an old (1998) s-news post from Dr. Terry Therneau describing a way to use coxph to model competing risks. I am re-producing the post at the bottom of this message. I would like to
2008 Jul 27
0
competing risk model with time dependent covariates under R or Splus
This message was also sent to the MEDSTATS mailing list, so here is the reply I posted to that: Philippe, The machinery to use is to split follow-up time so finely that you can safely assume that rates are constant in each interval, and then just stuff it all into a Poisson model. This allows you to use any kind of time-dependent variables as well as accommodating competing risks. In the Epi
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 -- View this message in context:
2006 Jul 11
2
Proportional Hazard Function and Competing risks
How can I model coxph() in combination with competing risks i.e. I have two events and for event the object will leave the data set. So : Coxph(Surv(time,event)~....) the event is for all my objects 1. How can I model this? Sharon ----------------------------------------------------------------- ATTENTION: The information in this electronic mail message is private and confidential, and only
2011 Jul 20
0
Competing risk regression with CRR slow on large datasets?
Hi, I posted this question on stats.stackexchange.com 3 days ago but the answer didn't really address my question concerning the speed in competing risk regression. I hope you don't mind me asking it in this forum: I?m doing a registry based study with almost 200 000 observations and I want to perform a competing risk analysis. My problem is that the crr() in the cmprsk package is
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
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)
2011 Jun 27
7
cumulative incidence plot vs survival plot
Hi, I am wondering if anyone can explain to me if cumulative incidence (CI) is just "1 minus kaplan-Meier survival"? Under what circumstance, you should use cumulative incidence vs KM survival? If the relationship is just CI = 1-survival, then what difference it makes to use one vs. the other? And in R how I can draw a cumulative incidence plot. I know I can make a Kaplan-Meier
2009 Jun 23
0
Fractional Polynomials in Competing Risks setting
Dear All, I have analysed time to event data for continuous variables by considering the multivariable fractional polynomial (MFP) model and comparing this to the untransformed and log transformed model to determine which transformation, if any, is best. This was possible as the Cox model was the underlying model. However, I am now at the situation where the assumption that the competing risks
2018 Feb 16
0
Competing risks - calibration curve
Hi, Sorry not to provide R-code in my previous mail. R code is below #install.packages("rms") require(rms) #install.packages("mstate") library(mstate) require(splines) library(ggplot2) library(survival) library(splines) #install.packages("survsim") require(survsim) set.seed(10) df<-crisk.sim(n=500, foltime=10, dist.ev=rep("lnorm",2),
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
2003 Dec 21
0
Software/algorithms for competing risks analysis
Dear R group: I am compiling a list of available algorithms/macros/software for performing the following types of competing risks analyses: (1) cumulative (crude) incidence regression (2) Gray's K-sample log-rank test for cmulative incidence (3) multi-state models (4) dependent competing risks modeling with (a) copulas, (b) Robin's Inverse probability of censoring weighted (IPCW)
2006 Nov 06
1
Competing risk nomogram
Dear R Users, Do you have a sample code for developing a nomogram with competing-risks? Any help is appreciated. Kind regards, ND Nguyen
2008 Jul 26
0
competing risk model with time dependent covariates
Dear R users, is there a way, I mean a package, to perform a competing risk model which can handle time dependent covariates ? my main covariate (additional treatment to patients) appears not to follow the proportional hazards assumption, its effect being observed after one year of treatment but not before (this is expected / makes sense on a clinical point of view). SO I was planning to use a
2018 Feb 16
0
Competing risks - calibration curve
Dear R users, I am new to R and wanted to apply competing risk methods in my research work. I used the R code given by Zhang et al in his paper 'Nomogram for survival analysis in the presence of competing risks published in Ann Trans Med 2017:5(20):403. I am struggling with getting calibration curve thro' internal validation. I am happy to receive suggestion in the coding as well
2018 Mar 21
0
selectFGR - variable selection in fine gray model for competing risks
Dear Raja, A Fine and Gray model can be fitted using the standard coxph function with weights that correct for right censoring and left truncation. Hence I guess any function that allows to perform stepwise regression with coxph should work. See e.g. my article in Biometrics https://doi.org/10.1111/j.1541-0420.2010.01420.x, or the vignette "Multi-state models and competing risks" in the
2018 Mar 18
1
selectFGR - variable selection in fine gray model for competing risks
Dear All, I would like to use R function 'selectFGR' of fine gray model in competing risks model. I used the 'Melanoma' data in 'riskRegression' package. Some of the variables are factor. I get solution for full model but not in variable selection model. Any advice how to use factor variable in 'selectFGR' function. The following R code is produced below