DESCRIPTION

Package: HHJMs
Type: Package
Title: H-likelihood-based hierarchical joint models
Version: 0.1.0
Author: Tingting Yu
Maintainer: Tingting Yu <tingting.yu.jun@gmail.com>
Description: This package fits shared parameter models for the joint modeling of longitudinal data and survival data, 
  where the longitudinal responses may be of mixed types, such as binary and continuous, and may be left censored by 
  lower limit of quantification. For statistical inference, we consider a computationally efficient approximate likelihood 
  method based on h-likelihood method. Essentially, the h-likelihood method uses Laplace approximations to the intractable 
  integral in the likelihood. Moreover, it can produce approximate MLEs for the mean parameters and approximate restricted 
  maximum likelihood estimates (REML) for the variance-covariance (dispersion) parameters. 
    We also implement the adaptive Gauss-Hermite method to compare with the h-likelihood method.
    A detailed example is given in the example folder.
License: What license is it under?
Encoding: UTF-8
Imports: 
  Deriv (>= 3.9.0),
  matrixcalc (>= 1.0-3),
  lbfgs (>= 1.2.1),
  parallel (>= 3.5.3)
LazyData: true
RoxygenNote: 7.0.2