search for: cencode

...llows where covaea and covaeb are matrices of covarites, all coded as binary variables. In case a: > covaea <- cbind(sexa,fsha,fdra,nsigna,eega,th1a,th2a,stype1a,stype2a,stype3a,pgu1a,pgu2a,log(agea),firstinta/1000,totsezbasea) > fita <- crr(snearma$with.Withtime,csaea,covaea,failcode=2,cencode=0) and in case b: > covaeb <- cbind(sexb,fshb,fdrb,nsignb,eegb,th1b,th2b,stype1b,stype2b,stype3b,stype4b,stype5b,pgu1b,pgu2b,(ageb/10)^(-1),firstintb,log(totsezbaseb)) > fitb <- crr(snearmb$with.Withtime,csaeb,covaeb,failcode=2,cencode=0) csaea and csaeb are the censoring indicators f...

...Correct me if I m wrong in trying to do so. First, I have run the following script (R2.7.1 under XPpro) according to previous advices: library(cmprsk) attach(LAMrelapse) fit1<- crr(rel.t, rel.s, treatment, treatment, function(uft) cbind(ifelse(uft<=1,1,0),ifelse(uft>1,1,0)), failcode=1, cencode=0, na.action=na.omit, gtol-06, maxiter) fit1 where: rel.t = time to event (in years) rel.s = status , =1 if disease relapse, =2 if death from non disease related cause (toxicity of previous chemotherapy), =0 if alive & not in relapse treatment = binary covariate (value: 0 or 1) representing th...

Hi all I do not understand why I am getting the following error message. Can anybody help me with this? Thanks in advance. install.packages("cmprsk") library(cmprsk) result1 <-crr(ftime, fstatus, cov1, failcode=1, cencode=0 ) one.pout1 = predict(result1,cov1,X=cbind(1,one.z1,one.z2)) predict.crr(result1,cov1,X=cbind(1,one.z1,one.z2)) Error: could not find function "predict.crr" [[alternative HTML version deleted]]

...t me if I m wrong in trying to do so. First, I have run the following script (R2.7.1 under XPpro) according to previous advices: library(cmprsk) attach(LAMrelapse) fit1<- crr(rel.t, rel.s, treatment, treatment, function(uft) cbind(ifelse(uft<=1,1,0),ifelse(uft>1,1,0)), failcode=1, cencode=0, na.action=na.omit, gtol-06, maxiter) fit1 where: rel.t = time to event (in years) rel.s = status , =1 if disease relapse, =2 if death from non disease related cause (toxicity of previous chemotherapy), =0 if alive & not in relapse treatment = binary covariate (value: 0 or 1) represent...

...atment withdrawal, with.Wcens is the censoring indictor for the event and all.firstint is the age at baseline. To look at the competing risks regression modelling when age in untransformed, I can use the following code: fitn<-crr(nearma$with.Withtime,censaeb,as.matrix(nearma$all.age),failcode=2,cencode=0) where censaeb is the censoring indicator which is coded 1 for the event of interest (time to treatment failure), 2 for the competing risk and 0 for the censored value. Can anyone suggest how I can effectively combine these situations i.e. is there a way to apply the fractional polynomail transf...

...rest) I want to investigate if pre has a significant impact on time to event for patients who died and for those who suffered disease progression (as well as it's impact on the overall time to event). The code I have used is as follows: fitd <- crr(dat1$ccr,dat1$Crcens,dat1$pre,failcode=1,cencode=0) fitp <- crr(dat1$ccr,dat1$Crcens,dat1$pre,failcode=2,cencode=0) In these cases I get p-values of 0 and 0.66 respectively. What I would now like to do, is to plot two cumulative incidence curves - one for the 'pre' variable status for patients who didn't acheive the event due to...

...gt; > > First, I have run the following script (R2.7.1 under XPpro) according to previous advices: > > library(cmprsk) > attach(LAMrelapse) > fit1<- crr(rel.t, rel.s, treatment, treatment, function(uft) > cbind(ifelse(uft<=1,1,0),ifelse(uft>1,1,0)), failcode=1, > cencode=0, na.action=na.omit, gtol-06, maxiter) > fit1 > > where: > rel.t = time to event (in years) > rel.s = status , =1 if disease relapse, =2 if death from non disease > related cause (toxicity of previous chemotherapy), =0 if alive & > not in relapse > treatment = > bin...

...K library. The default x-axis places tick marks and labels at 0, 20, 40, 60, and 80 (my data has an upper limit of 96), whereas I want them at my own specified locations. Here is my example code: library(cmprsk) attach(MYDATA) MYCUMINC <- cuminc(ftime=TIME,fstatus=STATUS,group=GROUP,rho=0,cencode=0,na.action=na.omit) plot(MYCUMINC,xlim=c(0,96),ylim=c(0,0.5),xlab="",axes=F) axis(1,at=c(0,8,16,24,32,48,72,96)) As you can see, I have tried using the "axes=F" parameter that works for most plotting functions, but I get the following error message: Error in legend(wh[1], w...

...----------- ERROR Errors in running code in vignettes: when running code in ?compete.Rnw? ... > temp$fstat <- as.numeric(event) > temp$msex <- with(temp, 1 * (sex == "M")) > fgfit1 <- with(temp, crr(etime, fstat, cov1 = cbind(age, + msex, mspike), failcode = 2, cencode = 1, variance = TRUE)) When sourcing ?compete.R?: Error: could not find function "crr" Execution halted * checking re-building of vignette outputs ... NOTE Error in re-building vignettes: ... Warning in coxph(Surv(futime, death) ~ group:age2 + sex + strata(group), : X matrix deem...

Hi All, I am running a scatter plot and trying to add a best fit line. I use an abline function, but get no line drawn over the points. I also get no error. I arm using V 2.10.0 on Windows 7. Here is my code, including the SAS transport file import: require (foreign) require (chron) require (Hmisc) require (lattice) clin <- sasxport.get("y:\\temp\\subset.xpt") attach(clin)

...>> when running code in ?compete.Rnw? >> ... >> temp$fstat <- as.numeric(event) >> >> temp$msex <- with(temp, 1 * (sex == "M")) >> >> fgfit1 <- with(temp, crr(etime, fstat, cov1 = cbind(age, >> + msex, mspike), failcode = 2, cencode = 1, variance = TRUE)) >> >> When sourcing ?compete.R?: >> Error: could not find function "crr" >> Execution halted >> >> * checking re-building of vignette outputs ... NOTE >> Error in re-building vignettes: >> ... >> Warning in...

Hi, I need to fit model using crr, however my covariate is categorical with 3 levels. I use crr(time,status,agesplit,failcode=1,cencode=0) where agesplit is defined as <20,21-29,>30 years, so it takes 0, 1 or 2 for each patient. I hoped to get estimated coefficients for the levels 1 and 2 w.r.t level 0 as in coxph. But, I didn't. Could someone please help me to use crr in this situation? Thanks a lot. Ruwanthi

...n ?compete.Rnw? >>>???... >>> temp$fstat <- as.numeric(event) >>> >>> temp$msex <- with(temp, 1 * (sex == "M")) >>> >>> fgfit1 <- with(temp, crr(etime, fstat, cov1 = cbind(age, >>> +? ???msex, mspike), failcode = 2, cencode = 1, variance = TRUE)) >>> >>>???When sourcing ?compete.R?: >>> Error: could not find function "crr" >>> Execution halted >>> >>> * checking re-building of vignette outputs ... NOTE >>> Error in re-building vignettes: >&g...