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joiner's Issues

Competing risks error

I am trying to use the package in the presence of competing risk.

I going through the issue that if I include more than one variable (x1+x2) in the survival model, I get an error saying that object x2 is not found. I tried also the epileptic data and I got the same error when I tried to include gender and age in the model

> data(epileptic)

longitudinal <- epileptic[, c(1:3)]
survival <- UniqueVariables(epileptic, c(4, 6), "id")
baseline <- UniqueVariables(epileptic, c(“age”,”gender”), "id")
data <- jointdata(longitudinal = longitudinal,
survival = survival,
baseline = baseline,
id.col = "id",
time.col = "time")

fit2 <- joint(data = data,
long.formula = dose ~ time,
surv.formula = Surv(with.time, with.status2) ~ gender+age,
longsep = FALSE, survsep = FALSE,
gpt = 3)
Error in eval(predvars, data, env) : object 'age' not found
In addition: Warning message:
In names(survdat2)[(ncol(survdat) + 1):ncol(survdat2)] <- attr(surv.terms, :
number of items to replace is not a multiple of replacement length

joineR in CR with multiple covariates

I tried the updated version, now the survival model doesn't read the first covariate in a list of multiple covariates to adjust for, the error is:
Error : in match.arg(model): object x1 not found.
I might be missing something

Fix sample.jointdata for case when ID is not first column in longitudinal data

A recent email alerted me to this issue. In our datasets the ID is always the first column so this doesn't arise. Using UniqueVariables for the survival and baseline components means it doesn't occur for those. However the longitudinal data has a requirement (implicit) that the ID is first and the sampling (in the bootstrap) fails otherwise. Should be a trivial solve.

Issues of running competing risks data

Hi, I encountered some issues when I was running your toy example data:

data(epileptic)
epileptic$interaction <- with(epileptic, time * (treat == "LTG"))
longitudinal <- epileptic[, c(1:3, 13)]
survival <- UniqueVariables(epileptic, c(4, 6), "id")
baseline <- UniqueVariables(epileptic, c("treat", "age"), "id")
data <- jointdata(longitudinal = longitudinal,
survival = survival,
baseline = baseline,
id.col = "id",
time.col = "time")
fit2 <- joint(data = data,
long.formula = dose ~ time + treat + interaction + age,
surv.formula = Surv(with.time, with.status2) ~ treat + age,
longsep = FALSE, survsep = FALSE,
gpt = 3)
summary(fit2)

Error in eval(predvars, data, env) : object 'age' not found

I want to build a survival sub-model with multiple covariates but I failed to do so. Do you know how to fix this issue?

Updates to jointSE

Things we should add:

  • Parallel processing
  • Catch errors + warnings, and re-run iterations caught

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