similar to: counting process form of a cox model (cluster(id))?

Hi there, I have a rather large data set and perform the following cox model: test1 <- list(tstart,tstop,death1,chemo1,radio1,horm1) out1<-coxph( Surv(tstart,tstop, death1) ~ chemo1+chemo1:log(tstop+1)+horm1+horm1:log(tstop+1)+age1+grade1+grade1:log(tstop+1)+positive1+positive1:log(tstop+1)+size1+size1:log(tstop+1), test1) out1 Up to here everything works fine (with each covariate

in wine/dlls/qcap/v4l.c: ReadThread() --> OutputPin_GetDeliveryBuffer((OutputPin *)capBox->pOut, &pSample, NULL, NULL, 0); --> IMediaSample_SetTime(*ppSample, tStart, tStop); in wine/dlls/quartz/memallocator.c: StdMediaSample2_GetTime(IMediaSample2 * iface, REFERENCE_TIME * pStart, REFERENCE_TIME * pEnd) --> if tstart/stop is NULL, leave pStart/pEnd not setted. in

> On Apr 16, 2018, at 3:20 PM, David Winsemius <dwinsemius at comcast.net> wrote: > >> >> On Apr 16, 2018, at 2:58 PM, Therneau, Terry M., Ph.D. via R-devel <r-devel at r-project.org> wrote: >> >> A user asked me about this and I can't figure it out. >> >> tmt% R >> R Under development (unstable) (2018-04-09 r74565) --

tftp-hpa-0.35 and tftp-hpa-0.36 show wrong transmission time. >tftp -V tftp-hpa 0.36, with readline >tftp -m octet -v localhost -c get aaa /tmp/aaa Connected to localhost.localdomain (127.0.0.1), port 69 getting from localhost.localdomain:aaa to /tmp/aaa [octet] Received 33554432 bytes in -3.3 seconds [-81407477 bit/s] ^^^^ ^^^^^^^^^ By the way, why

  Hi there,   I am beginner in R and I have some basic question. Suppose I run a common procedure such as a t test or cox model like below:   out<-coxph( Surv(tstart,tstop, death1) ~ x1+x1:log(tstop+1) , test1,method=c("breslow"))    Which yields the following result:   Call: coxph(formula = Surv(tstart, tstop, death1) ~ x1 + x1:log(tstop +     1), data = test1, method =

Hi everyone, I was trying to mode the following exercise using R. The question: Set up a one pool model using numericintegration. The model will run from time 1 to time 30 using a time step of 1.The pool (A) will be fed by flux "inA" at a rate of 5 units per hour anddrained by flux "outA" at a rate of 20% per hour. At time 0, A has 5units. At time 30, what is the pool size of

Hi , I have a data set with recurrence time (up to four) of myocardial infarction (MI). Part of the file is showing below: Num1 Trt Sex Time T1 T2 T3 T4 1011 1 1 9 1211 0 1 59 3020 1 2 14 3 1245 0 1 18 12 16 3069 1 2 26 6 12 13 2051 0 1 53 3 15 46 51 The data consist of the following eight variables: Num1 , patient number Trt, treatment group (1=placebo and 2=drug) Sex,

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),

Zoe writes: My question is quick. I am looking at 1 event (death), and repeated measurements (the time dependent covariate 'lqol') are frequently taken on a subject, so I assume that measurements on the same subject will be correlated. The answer is: no, it's not a problem When the time intervals for a subject are disjoint, e.g, 0-10, 10-49, 49-127, etc, like they will be on this

Hello, I have a cohort with approx 1,200 patients at the ages of 30-65 that had their first myocardial infarction during 1992: · They were in a follow up until 2005. · About 400 of them died during this period of time (right censored) · Each one of them had up to 4 mi recurrent events. I am using the semi-parametric model in order to assess the relationship of

Hi, when i run the following code i get this massege: "The instruction at 0x######## reference memory at 0x#######, the memory cannot be "read". and then i have to close R. what is the problem and how can i solve it? thanks in advance Avi my code # frailtypack library(frailtypack) cgd.ag <- read.csv("C:/rfiles/RE/cgd.csv") cgd.nfm <-frailtyPenal(Surv(TStart,

A user asked me about this and I can't figure it out. tmt% R R Under development (unstable) (2018-04-09 r74565) -- "Unsuffered Consequences" Copyright (C) 2018 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) > library(survival) > data(cgd0) Warning message: In data(cgd0) : data set ?cgd0? not found ---- The data set is present and can be

Dear R Community, I am attempting to transpose a dataset from rows to columns but am stuck. I have tried using reshape() with little luck, possibly due to the categorical nature of the data. For example: id<-c(1,2,2,3,3,3) author<-c("j","k","k","l","l","l")

Dear users, In a study with recurrent events: My objective is to get estimates of survival (obtained through a Cox model) by rank of recurrence and by treatment group. With the following code (corresponding to a model with a global effect of the treatment=rx), I get no error and manage to obtain what I want : data<-(bladder)

I would like to have your comments regarding: 1) drivers/rhino.c ------------------ The following patch addresses some problems in drivers/rhino.c. Or that is what I think. I don't use this hardware. The patch: 1. Eliminates some usefulness definitions. 2. It removes code that evaluate the time. I can't see how the code actually does useful work. 3. The

It would be nice if the 00check.log file also included this part of the output: Running ?bladder.R? Comparing ?bladder.Rout? to ?bladder.Rout.save? ... OK Running ?book1.R? Comparing ?book1.Rout? to ?book1.Rout.save? ... OK Running ?book2.R? Comparing ?book2.Rout? to ?book2.Rout.save? ... OK etc. The survival package has enough test scripts that it exceeds my terminal's scroll

Hi All, I'm working with some SAS code to analyze an experiment set up as follows: 66 subjects (colonies) treated with a random treatment (1-8) and measured at three time points. The data structure looks like: input colony tmt y1 y2 y3; y=y1; date=*1*; output; y=y2; date=*2*; output; y=y3; date=*3*; output; datalines; 1

I have a nested ANOVA, with a fixed factor "tmt" nested within "site" (random). There are missing values in the data set. aeucs, tmt and site have been defined as objects I have tried: model1=lme(aeucs~tmt,random=~1|tmt/site) I get the following error message Error in na.fail.default(list(aeucs = c(0.833333333, 1, 1, 1, 1, 1, 0.666666667, : missing values in object I

Dear all, in order to estimate transition-specific probabilities in a multi-state model i applied the 'probtrans()' function from the 'mstate'-package. Now, i am at loss with the following message (see attached example): Warning message: In probtrans(msf.0, predt = 0) : Negative diagonal elements of (I+dA); the estimate may not be meaningful. I am not very familiar with matrix

Hello R-help. I am trying to make a stacked barplot where the color of the sections of each bar depend on another variable. > myData[1:11,] score percent marker cellType Malignant 1 0 100.00000 ESR1 (ER) Bladder.M(5) TRUE 2 0 80.00000 PAX8 Bladder.M(5) TRUE 3 1 20.00000 PAX8 Bladder.M(5) TRUE 4 0 100.00000 ESR1 (ER) Brain.N(3) FALSE 5 0