search for: timereg

Hi all, I've been reading and using the information from the list for some time but this is my first question here. English is not my primary language, so sorry in advance for any language mistakes. :) I'm working with the "timereg" package to analize survival data. I want to perform a multivariate analisis of clinical information similar to the Cox regression but taking competing risks into account. I have taken a look to the documentation of the package and decided to use the Fine and Gray model and I use the command...

Dear R-helpers: I am trying to use aalen{timereg} to run a model and found that it generates the following message. the data set I used is > dim(indf) [1] 13743 10 #R code: fit_aalen <- aalen(Surv(durdxdeathp, die) ~ 1+factor(gender), indf) #start of error message below Non unique survival times: break ties ! Break ties yourself Error i...

Hello again, I m trying to use timereg package as you suggested (R2.7.1 on XP Pro). here is my script based on the example from timereg for a fine & gray model in which relt = time to event, rels = status 0/1/2 2=competing, 1=event of interest, 0=censored random = covariate I want to test library(timereg) rel<-read.csv("r...

...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 repeating myself, sorry). I can't seem to find a package or function that can handle 2 competing risks for the main event. I realize I may be using the well-known ones, timereg and cmprisk, wrong. And if I am, then I'd appreciate a correction. Here's the model I tried (and it crashes) comp.risk(Surv(futime, retention==2) ~ sex, data=dta, dta$retention, causeS=c(1,3), resample.iid=1, n.sim=100) I apologize, but I am cannot create the example dataset using code....

Hello, I have a problem regarding calculation of Cumulative Incidence Function. The event of interest is failure of bone-marrow transplantation, which may occur due to relapse or death in remission. The data set that I have consists of- lifetime variable, two indicator variables-one for relapse and one for death in remission, and the other variables are donor type (having 3 categories), disease

...Rmpi Rssa TR8 VarEff > aoristic breakage dplyr effects ftsa geocodeHERE ggHorizon ggmap > ggtern gvcm.cat hyperSpec knitcitation knitr mboost mets mfblock > mobForest mra nontarget npRmpi nullabor openNLP parfm plsRbeta powerr > pxweb rcrossref rgbif rsnps season spMC spgwr spocc taxize timereg > toaster > > and warnings in DSpat > > In almost all cases there is something obviously wrong with the > failing example. > > Please submit an update to CRAN (using the webform, and following the > CRAN policies at http://cran.r-project.org/web/packages/policies.html). &...

...ing causes: P_k1(t; x)=P(T<=t, cause=k1|x)=Sum(u=0, ..., u=t) {hazard_k(u;x)*S(u;x)} where S(u;x) = exp{-sum_of_k(sum(hazard_k(u))} I have searched extensively for an implementation of this in many packages, but it appears that more complex approaches are more commonly implemented, such as timereg package. Eleni Rapsomaniki Research Associate Strangeways Research Laboratory Department of Public Health and Primary Care University of Cambridge [[alternative HTML version deleted]]

Hi I have been asked to perform a multivariate survival analysis with competing risks. We used to use the Cox Regression from SPSS. To perform this new analysis I'm using the comp.risk function from the timereg package. I have managed to use it and get the final model and the correct P values, but I cannot find anything like the Exp(B) (the Hazard Ratio) in the function's result. Anyone knows how can I get the Hazard ratios and how? are they related somehow to (and maybe can be derived from) the '...

Dear Sir, I am using timereg package for analysing competing risk data. There are two options in method: proportional and additive. How to choose among the methods for analysis and how to check which of the methods are appropiate for the specific data. Tanks a lot. Dr Suman Kumar [[alternative HTML version deleted]]

...> > aoristic breakage dplyr effects ftsa geocodeHERE ggHorizon ggmap > > ggtern gvcm.cat hyperSpec knitcitation knitr mboost mets mfblock > > mobForest mra nontarget npRmpi nullabor openNLP parfm plsRbeta powerr > > pxweb rcrossref rgbif rsnps season spMC spgwr spocc taxize timereg > > toaster > > > > and warnings in DSpat > > > > In almost all cases there is something obviously wrong with the > > failing example. > > > > Please submit an update to CRAN (using the webform, and following the > > CRAN policies at http://cran...

Dear R users, I d like to assess the effect of "treatment" covariate on a disease relapse risk with the package cmprsk. However, the effect of this covariate on survival is time-dependent (assessed with cox.zph): no significant effect during the first year of follow-up, then after 1 year a favorable effect is observed on survival (step function might be the correct way to say that ?).

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

Dear List: I have a data frame prepared in the couting process style for including a binary time-dependent covariate. The first few rows look like this. PtNo Start End Status Imp 1 1 0 608.0 0 0 2 2 0 513.0 0 0 3 2 513 887.0 0 1 4 3 0 57.0 0 0 5 3 57 604.0 0 1 6 4 0 150.0 1 0 The outcome

CRAN (and crantastic) updates this week New packages ------------ * disclapmix (0.1) Maintainer: Mikkel Meyer Andersen Author(s): Mikkel Meyer Andersen and Poul Svante Eriksen License: GPL-2 http://crantastic.org/packages/disclapmix disclapmix makes inference in a mixture of Discrete Laplace distributions using the EM algorithm. * EstSimPDMP (1.1) Maintainer: Unknown Author(s):

...rvey (3.22-2), SV (1.2.4), svcR (1.6.4), svGUI (0.9-47), svIDE (0.9-49), svMisc (0.9-57), svUnit (0.7-2), SweaveListingUtils (0.4.5), tawny (1.2.1), tdm (2.2.2), tensorA (0.35), termstrc (1.3.1), textcat (0.0-3), tgp (2.3-3), TGUICore (0.9.10), TGUITeaching (0.9.10), time (1.1), timeDate (2120.89), timereg (1.3-4), timeSeries (2120.88), tis (1.12), tm.plugin.mail (0.0-3), tnet (2.7.1), tolerance (0.2.1), topicmodels (0.0-6), topmodel (0.7.2-1), tpr (0.3-1), tractor.base (1.5.0), traitr (0.7), tree (1.0-28), trio (1.1.10), trip (1.1-6), tripEstimation (0.0-33), truncnorm (1.0-4), TSdbi (2010.5-1), tsD...