Suggests: broom, covr, ggplot2, knitr, lmerTest, rmarkdown, testthat,

Title: Regression Analysis of Grouped and Coarse Data
Author: Dimitris Rizopoulos <dimitris.rizopoulos@med.kuleuven.be> and Spyridoula Tsonaka <spyridoula.tsonaka@med.kuleuven.be>
Description: Regression models for grouped and coarse data, under the Coarsened At Random assumption.
Packaged: Mon Aug  8 09:50:38 2005; dimitris

Packaged: Tue Aug 16 09:31:13 2005; dimitris

Packaged: Fri Sep  2 10:20:38 2005; dimitris

Packaged: Mon Sep 11 16:26:26 2006; dimitris

Author: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl> and Spyridoula Tsonaka <spyridoula.tsonaka@med.kuleuven.be>
Packaged: Mon Sep 15 09:30:51 2008; Dimitris

Packaged: Mon Jan 26 11:08:55 2009; Dimitris

Author: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl> and Spyridoula
Description: Regression models for grouped and coarse data, under the

Title: Efficient Estimation of Grouped Survival Models Using the Exact
Description: The core of this 'Rcpp'-based package is a set of functions to compute the efficient score statistics for grouped survival models. The functions are designed to analyze grouped time-to-event data with the optional inclusion of either baseline covariates or family structure of related individuals (e.g., trios). Functions for estimating the baseline hazards, frailty variance, nuisance parameters, and fixed effects are also provided. The functions encompass two processes for discrete-time shared frailty model data with random effects: (1) evaluation of the multiple variable integration to compute the exact proportional-hazards-model-based likelihood and (2) estimation of the desired parameters using maximum likelihood. For data without family structure, only the latter step is performed. The integration is evaluated by the 'Cuhre' algorithm from the 'Cuba' library (Hahn, T. (2005). Cuba-a library for multidimensional numerical integration, Comput. Phys. Commun. 168, 78-95 <doi:10.1016/j.cpc.2005.01.010>), and the source files of the 'Cuhre' function are included in this package. The maximization process is carried out using Brent's algorithm, with the 'C++' code file from John Burkardt and John Denker (Brent, R., Algorithms for Minimization without Derivatives, Dover, 2002, ISBN 0-486-41998-3).
Imports: Rcpp (>= 0.12.4), doParallel, doRNG, parallel, foreach, qvalue