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jlctree (version 0.0.2)

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

Description

Implements the tree-based approach to joint modeling of time-to-event and longitudinal data. This approach 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. See Zhang and Simonoff (2018) .

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Version

Install

install.packages('jlctree')

Monthly Downloads

61

Version

0.0.2

License

GPL

Maintainer

Ningshan Zhang

Last Published

April 15th, 2021

Functions in jlctree (0.0.2)

survi

Defines the initialization function for a new splitting method of rpart.
jlctree.control

Sets the control parameters for jlctree.
survs

Defines the splitting function for a new splitting method of rpart.
get_node_val

Computes the test statistic at the current node.
surve

Defines the evaluation function for a new splitting method of rpart.
get_lrt

Computes the likelihood ratio test statistic.
prune_tree

Prunes an rpart tree to have the desired number of nodes.
data_timevar

A simulated dataset with time-varying longitudinal outcome and covariates.
get_wald

Computes the Wald test statistic.
jlctree

Fits Joint Latent Class Tree (JLCT) model.
data_timeinv

A simulated dataset with time-invariant longitudinal outcome and covariates.
jlctree-package

Fits Joint Latent Class Tree (JLCT) model.