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License: GNU General Public License v3.0
This project forked from graemeleehickey/joiner
License: GNU General Public License v3.0
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
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
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.
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?
TravisCI is no longer being adopted for R packages. We should use GitHub actions, which is automated by the usethis package.
Currently joineR does not allow the user to include polynomials or other functional forms in the survival sub-model. Note that the longitudinal sub-model does allow this.
Things we should add:
Currently no SEs are provided by default.
Currently joineR throws an error if the user wishes to fit a model where the longitudinal response is transformed or scaled etc.
joineR looks a little dated next to newer packages and the summary feature could do with an upgrade.
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