similar to: Problem of COX model with time dependent covariate

> Dear All, > > I have built a survival cox-model, which includes a covariate * time interaction. (non-proportionality detected) > I am now wondering how could I most easily get survival predictions from my model. > > My model was specified: > coxph(formula = Surv(event_time_mod, event_indicator_mod) ~ Sex + > ageC + HHcat_alt + Main_Branch + Acute_seizure +

Hi I have the following formula (I hope it is clear - if no, I can try to do better the next time) h(x, a, b) = integral(0 to pi/2) ( ( integral(D/sin(alpha) to Inf) ( ( f(x, a, b) ) dx ) dalpha ) and I want to do an mle with it. I know how to use mle() and I also know about integrate(). My problem is to give the parameter values a and b to the

Dear R-helpers, an rgl-ers in particular, what is the easiest way to plot a section of a plane in 3D, that is given by the xyz coordinates of the outline? Suppose I have a polygon - which I know for sure is a set of coordinates on the same plane. One method I found is to use surf.tri from the geometry package, and then plot the triangles with rgl.triangles. This method is not perfect though,

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 [[alternative HTML version deleted]]

Hi All, I'm learning the R codes for Cox PH modeling. Could I ask you what the function of "factor" in modeling? Thank you! When dealing with the categorical covariates (for example 3 groups), it will come out different results if we add the command "factor" in front of the categorical covariate or not: if we don't add "factor", there is only one

dears, I like two write a program with R to estimate the coefficients of covariate,I like two know the original program for this programing for partial maximum likelihood for cox models with two co variate. I did it with coxph command, thanks [[alternative HTML version deleted]]

Hello All, Does anyone know where I can find information about how to do a power analysis for Cox regression with a time-varying covariate using R or some other readily available software? I've done some searching online but haven't found anything. Thanks, Paul

To enhance my understanding, and that of my students, I have a question about cox.zph in the survival package. If I have correctly gleaned the high-level point from the 1994 Biometrika paper of Grambsch and Therneau, it looks to me like cox.zph provides a mechanism to test for a simple trend in plots of a function of time, g(t) versus the scaled schoenfeld residuals and it also provides some

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

Hello Everyone,   I'm learning how to perform various statistical analyses in R. I'm checking my understanding by replicating examples from my SAS books. Below is an attempt to replicate a Cox Proportional Hazards model with a time-varying covariate. I think I'm doing this correctly but am not completely sure. I would appreciate it if someone could double-check my results. In case

This is a question about the use of the Cox proportional hazards model to analyze event histories. I am looking at the responses of sympathetic nervous system activity to a stimulus. The activity I observe is a burst that can only occur once per heart beat cycle (e.g., a binary count). Typically bursts occur in 60-80% of the heart cycles * sensory stimuli can modify these burst probabilities.

I am in the process of transferring from an old version of S+ to using R having used a variety of other packages in the past. I'm hugely impressed with R but it has an excellent but depressing habit of exposing that I'm not a professional statistician and has done so again. Someone has run a nice little repeated measures design on my advice, students randomised to four orders of a

Hello everyone, I am searching for a covariate selection procedure in a cox model formulated as a counting process. I use intervals, my formula looks like coxph(Surv(start,stop,status)~ x1+x2+...+cluster(id),robust=T) where id is a country code (I study occurence of civil wars from 1962 to 1997). I'd like something not based on p-values, since they have several flaws for this purpose. I turned

Building the current release 2.7 branch on x86_64-apple-darwin10 with r81455 reverted, I get the following Polyhedron 2005 benchmark results (with no test failures)... ================================================================================ Date & Time : 7 Apr 2010 22:24:16 Test Name : llvm_gfortran_lin_p4 Compile Command : llvm-gfortran -ffast-math -funroll-loops -msse3

Risk report: Two years of Red Hat Enterprise Linux 4 by Mark Cox http://www.redhatmagazine.com/2007/04/18/risk-report-two-years-of-red-hat-enterprise-linux-4/ -- Paul Norton System Administrator Neoverve

The various ac patches have had ext3 for some time. What is the difference between using Alan's patches vs the ext3 patches?

Hi I am doing a survival analysis and have run into a couple of things that I was hoping I could get some advice on. The first thing is that when I run an ordinary Cox regression in R I get the same results that I do using Stata (provided that I specify the Efron method for handling ties) but I also get the following warning message: "Warning message: In coxph(Surv1 ~ Out + site + haem) :

Hello I am using box.cox() and I get this error message: Warning message: 'box.cox' is deprecated. Use 'bcPower' instead. See help("Deprecated") and help("car-deprecated"). I went to help but I did not understand the explanation, I am still wondering what is really happening. Thanks /R

I also hope to get the code of using lasso method in the cox model.Could you please send me one? Thank you so much!!!

Hi, I've generated a cox model, but I'm struggling to work out how to output predctions based on the model I've made. my.model<-coxph(Surv(duration,status) ~ gender + var1 + var2, data=mydata) My test data set looks something like this: id,actualduration,gender,var1,var2 a,65,m,1,3 b,34,f,1,5 ... What i need to do is for each id, output a predicted duration based on my cox