similar to: Teasing out logrank differences *between* groups using survdiff or something else?

The survival package makes significant use of the "specials" argument of terms(), before calling model.frame; it is part of nearly every modeling function. The reason is that strata argments simply have to be handled differently than other things on the right hand side. Likewise for tt() and cluster(), though those are much less frequent. I now get "bug reports" from the

Hi list, I want to use the p-value from the survdiff function (package survival) to reuse within a function in a Kaplan-Meier plot. The p-value is somehow not a component of the value list ?! Thanks in advance -- A. Goralczyk G?ttingen, Ger.

how do l programme the logrank test. l am trying to compare 2 survival curves --------------------------------- [[alternative HTML version deleted]]

Hi everyone!! I have dataset composed of a numbers of survival analyses. ( for batch survival analyses by using for-loop) . Here are code !! ####### dim(svsv) Num_t<-dim(svsv) Num<-Num_t[2] # These are predictors !! names=colnames(svsv) for (i in 1:Num ) { name_tt=names[i] survdiff(Surv(survival.m, survival) ~ names[i], data=svsv) fit.Group<-survfit(Surv(survival.m, survival) ~

ExpeRts, I'm trying to compare three survival curves using the function "survdiff" in the survival package. Following is my code and corresponding error message. > survdiff(Surv(st_months, status) ~ strata(BOR), data=mydata) Error in survdiff(Surv(st_months, status) ~ strata(BOR), data = mydata) : No groups to test When I check the "strata" of the variable. I get .

--- included message ---- Thus, my question is: *What common measures exists for ranking/measuring variable importance of participating variables in a CART model? And how can this be computed using R (for example, when using the rpart package)* ---end ---- Consider the following printout from rpart summary(rpart(time ~ age + ph.ecog + pat.karno, data=lung)) Node number 1: 228 observations,

Hello, I am trying to set up a loop that can run the survdiff function with the ultimate goal to generate a csv file with the p-values reported. However, whenever I try a loop I get an error such as "invalid type (list) for variable 'survival_data_variables[i]". This is a subset of my data: structure(list(time = c(1.51666666666667, 72, 72, 25.7833333333333, 72, 72, 72, 72, 72,

Dear all, Does anyone knows how I could extract the p-value in: > survdiff(Surv(tempo,status) ~ grupo,data=dados1,rho=1) Call: survdiff(formula = Surv(tempo, status) ~ grupo, data = dados1, rho = 1) N Observed Expected (O-E)^2/E (O-E)^2/V grupo=1 21 5.12 12.00 3.94 14.5 grupo=2 21 14.55 7.68 6.16 14.5 Chisq= 14.5 on 1 degrees of freedom,

I read through Harrington and Fleming (1982) but it is beyond my statistical comprehension. I have survival data for insects that have a very finite expiration date. I'm trying to test for differences in survival distributions between different groups. I understand that the medical field is most often dealing with censored data and that survival analysis, at least in the package survival,

The number of recent questions from umn.edu makes me wonder if there's homework involved.... Simpler for your example is to use get and subset. dat <- structure(..... as found below var.to.test <- names(dat)[4:6] #variables of interest nvar <- length(var.to.test) chisq <- double(nvar) for (i in 1:nvar) { tfit <- survdiff(Surv(time, completion==2) ~

dear all, I would like to know whether survdiff and survReg function in the survival package work for left-truncated and right-censored data. If not, what other functions can i use to make comparison between two survival curves with LTRC data. thanks for any help given sing yee

I have a dataset which for the sake of simplicity has two endpoints. We would like to test if two different end-points have the same eventual meaning. To try and take an example that people might understand better: Lets assume we had a group of subjects who all received a treatment. The could stop treatment for any reason (side effects, treatment stops working etc). Getting that data is very

hie is it possible to get the code for the logrank test l just need the chisquared value. thanks --------------------------------- [[alternative HTML version deleted]]

Hi Does anyone know if there is a function like survdiff which can also handle left-truncated and right-censored data? When I use it on left-truncated and right-censored data I get an error message saying Right censored data only. Many thanks Rajen [[alternative HTML version deleted]]

Hello, As I am quitte an ignorant user of R, excuse me for any wrongfull usage of all the terms. My question relates to the statistics behind the survdiff function in the package survival. My textbook knowledge of the logrank test tells me that if I want to compare two survival curves, I have to take the sum of the factors: (O-E)^2/E of both groups, which will give me the Chisq. If I calculate

Hello! I want to compare two Kaplan-Meier-Curves by using the Logrank-Test: logrank(Surv(time[b], status[b]) ~ group[b]) This way I only get the value of the test-statistic, but not the p-value. Does anybody know how I can get the p-value? Thanks in advance! Verena Hoffmann

Hello R helpers: *My first message didn't pass trough filter so here it's again* I would like to obtain probability of an event for one single patient as a function of time (from survfit.coxph) object, as I want to find what is the probability of an event say at 1 month and what is the probability of an event at 80 months and compare. So I tried the following but it fails miserably. I

Hi, I am new to model selection by coefficient shrinkage method such as lasso. And I became particularly interested in variable selection in Cox regression by lasso. I became aware of the coxpath() in R package glmpath does lasso on Cox model. I have tried the sample script on the help page of coxpath(), but I have difficult time understanding the output. Therefore, I would greatly appreciate if

Dear Prof. Therneau I was impressed to discover that the 'survConcordance' now handles Surv() objects in counting format (example below to clarify what I mean). This is not documented in the help page for the function. I am very curious to see how a c-index is estimated in this case, using just the linear predictors. It was my impression that with left truncation the ordering of

Hi, I am using rpart as a part of my masters' project. I am trying to print out the resulting model using plot() function along with text() function. I am having difficulties with labels being cut-off. In text() function, I am using use.n=T option to get the number of people in each nodes but the on the lower and left part of the plot, the numbers get cut off. Thanks! Linus [[alternative