jlctree-package: Fits Joint Latent Class Tree (JLCT) model.

In jlctree: Joint Latent Class Trees for Joint Modeling of Time-to-Event and Longitudinal Data

Description

Fits Joint Latent Class Tree (JLCT) model. The main function of this package is jlctree.

Problem setup

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. Nevertheless, jlctree also allows data with time-invariant longitudinal outcome and covariates.

JLCT model

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.

Time-to-event data format

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 specified in survival, classmb, fixef, and ranef 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 tmerge in R package survival. See the simulated data_timevar and data_timeinv for examples of LTRC format and right-censored format respectively.

References

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).

See Also

jlctree, data_timeinv, data_timevar

jlctree documentation built on April 15, 2021, 5:06 p.m.