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Questions tagged [survival]

Survival analysis compares the statistical strength of predictors for events encoded as occuring or censored in concert with a time variable. It can be parametric or non-parametric.

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Reshaping longitudinal dataset with tmerge or SurvSplit?

I'm attempting to conduct survival analysis with time-varying covariates. The data comes from a longitudinal survey that is administered annually, and I have manipulated it to look like this: id event end.time income1 income2 …
Ryan
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gestate doesn't recognize numeric variable

I have a survival dataset and want to use package gestate for analysis. When I intent to fit model I obtain: fit2 <- fit_tte_data(data=survdata,Time="dias",Event="entrega",censoringOne=F,type="automatic") Error in Surv(T, E) : Time variable is not…
panchtox
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use labels in cox regression results

Trying to add labels to variable name to make it more coherent when displaying results The following library(survival) data(lung) Hmisc::label(lung$sex) <- "Gender" res.cox <- coxph(Surv(time, status) ~ as.factor(sex) , data =…
Edi Itelman
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Getting the error (subscript) logical subscript too long

I'm trying to run the following code, but I got this error Error in unclass(x)[i, , drop = FALSE] : (subscript) logical subscript too long library ( survival ) library(KMsurv) data("tongue") tongue Weibull.1<-survreg(Surv(times,censor)~1,…
Dana
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simsurv R function: is there a way to define different censor rates?

I'm trying to generate a few simulated survival datasets. I've chosen the simsurv function as it allows me to generate time varying coefficients (and hence non-proportional hazards). However, how do I go about defining different censor rates (10%,…
Kay
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Error using rmst2 function (restricted mean survival time) from survRM2 package

I am looking to compare two survival curves using the restricted mean survival time in R. As such, I am using the survRM2 package and following this R vignette. I am able to obtain the unadjusted analysis, as in section 3.1, by…
Mateus
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Get a 'survfit' object which will be the same size than the original data in case of ties? (survival, R)

I want the survival probability estimated by Kaplan-Meier estimator for each individual of my dataframe. The survfit(Surv(.)) function calculates the survival probability for each unique time ordered by decreasing order. What would be an elegant…
Flora Grappelli
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Competing risk survival curves: R vs Stata

I have done a competing risk survival analysis both with R and Stata. I have two cohorts of patients. However when plotting the curves I obtained very different results. For R I used the command cuminc(ftime,fstatus,group,cencode=0) and then…
Nico
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Time-varying covariates: formatting for one categorical variable with 3 levels

(This is an edited version of a previously closed question) I have a data.frame (condensed to testdata) of several demographic variables in addition to one variable with three levels for three possible comorbidities.…
Mircea_cel_Batran
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Issue with R Shiny App --> Interactive Survival Plots

I am new to R Shiny and I am trying to build a Shiny Web App that produces a survival plot with two reactive inputs. The first input is the study (total=4). The second input is the groups (total=19) to compare survival curves. Ideally, these two…
user2813606
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Is Accelerated Failure Time (AFT) method acceptable for answering my study question (an example)?

I need to conduct an adjusted survival analysis, however, Cox PH assumption was not met and data stratification isn't a good solution as one of my study groups already has a small number of patients. Thus, I tried to fit my first AFT model, however,…
st4co4
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Cox Hazard Model: why multiple factor levels are reference?

When conducting a multivariate Coxph model with categorical predictors, and after releveling all predictor variables (function= relevel()), two of my predictor variables have multiple levels that are "references", eliminating several analyses.…
SpencerS
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conducting a Tukey test on R

I'm trying to a Tukey test on the data (bmt), (KMsurv) and focusing on the variables t2 and d3 only. t2: the disease free survival time (time to relapse, death or end of study) d3: indicator variable for disease free. d3 = 1 if dead or relapsed,…
Heidi
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Post-hoc pairwise

I'm trying to conduct a post-hoc (multiple comparison) analysis on the data (bmt), (KMsurv) and focusing on the variables t2 and d3 only. Here is the code used: library(KMsurv) data(bmt) bmt library(survival) # run the ANOVA and print out the ANOVA…
Heidi
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Testing the hypothesis that there is no difference in survival between groups

I am trying to test the hypothesis that there is no difference in survival between the four groups in the data (kidney), reported on the death times of 863 kidney transplant patients. Where patients can be classified by race and sex into one of four…
Heidi
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