Fits Joint Latent Class Tree (JLCT) model.
The main function of this package is
The dataset contains three types of variables about each subject:
the time-to-event, the longitudinal outcome, and additional covariates.
The goal is to jointly model the time-to-event by a survival model
and the longitudinal outcomes by a linear mixed-effects model,
and using the additional covariates.
The longitudinal outcomes consist of repeated measurements, thus
are expected to be time-varying for a given subject.
The additional covariates can be either time-invariant or time-varying.
jlctree also allows data with time-invariant longitudinal outcome
This package implements the Joint Latent Class Tree (JLCT) modeling approach. JLCT assumes that the population consists of homogeneous latent classes; within a latent class subjects follow the same survival and linear mixed-effects model, but those differ from class to class. In addition, JLCT assumes that conditioning on latent class membership, time-to-event and longitudinal outcomes are independent. JLCT looks for a tree-based partitioning such that within each estimated latent class defined by a terminal node, the time-to-event and longitudinal responses display a lack of association. Once the tree is constructed, JLCT assigns each observation to a latent class (i.e. terminal node), and independently fits survival and linear mixed-effects models, using the class membership information.
The time-to-event data format required by
jlctree depends on the
time-varying nature of the variables to use:
if longitudinal outcome, or any of the covariates
is time-varying, then the time-to-event data must be in left-truncated right-censored (LTRC) format.
Otherwise, when longitudinal outcome and all of the covariates are time-invariant,
there should be only one observation per subject, and the time-to-event data
can either be in LTRC format (when there exits subject-specific entry time) or in
standard right-censored format.
To construct time-to-event data in left-truncated right-censored format, consider using function
See the simulated
data_timeinv for examples
of LTRC format and right-censored format respectively.
Ningshan Zhang and Jeffrey S. Simonoff: Joint Latent Class Trees: A Tree-Based Approach to Joint Modeling of Time-to-event and Longitudinal Data. arXiv:1812.01774 (2018).
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