Description Usage Arguments Value See Also Examples
Fits Joint Latent Class Tree model.
This is the main function that is normally called by the user.
See jlctreepackage
for more details.
1 2 
survival 
a twosided formula object; required. The left side of the formula corresponds
to a 
classmb 
onesided formula describing the covariates in the classmembership tree construction; required.
Covariates used for tree construction are separated by 
fixed 
twosided linear formula object for the fixedeffects in the linear mixedeffects model for
longitudinal outcomes; required.
The longitudinal outcome is on the left of 
random 
onesided formula for the nodespecific random effects in the linear mixedeffects model for
longitudinal outcomes; optional.
If missing, there are no nodespecific random effects in the fitted linear mixedeffects model.
Covariates with a random effect are separated by 
subject 
name of the covariate representing the subject identifier; optional. If missing, there are no subjectspecific random intercepts in the fitted linear mixedeffects model for longitudinal outcomes. 
data 
the dataset; required. 
parms 
parameter list of Joint Latent Class Tree model parameters.
See also 
control 

A list with components:
tree 
an 
control 
the 
parms 
the 
lmmmodel 
an 
coxphmodel_diffh_diffs 
a 
coxphmodel_diffh 
a 
coxphmodel_diffs 
a 
jlctreepackage, jlctree.control, rpart.control
1 2 3 4 5 6 7 8 9 10 11 12 13  # Timetoevent in LTRC format:
data(data_timevar)
tree < jlctree(survival=Surv(time_L, time_Y, delta)~X3+X4+X5,
classmb=~X1+X2, fixed=y~X1+X2+X3+X4+X5, random=~1,
subject='ID',data=subset(data_timevar, ID<=30),
parms=list(maxng=4, fity=FALSE, fits=FALSE))
# Timetoevent in rightcensored format:
data(data_timeinv)
tree < jlctree(survival=Surv(time_Y, delta)~X3+X4+X5,
classmb=~X1+X2, fixed=y~X1+X2+X3+X4+X5, random=~1,
subject='ID', data=subset(data_timeinv, ID<=30),
parms=list(maxng=4, fity=FALSE, fits=FALSE))

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