SemiCompRisks: Hierarchical Models for Parametric and Semi-Parametric Analyses of Semi-Competing Risks Data

Hierarchical multistate models are considered to perform the analysis of independent/clustered semi-competing risks data. The package allows to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions and cluster-specific random effects distribution; a Markov or semi-Markov specification for terminal event following non-terminal event. While estimation is mainly performed within the Bayesian paradigm, the package also provides the maximum likelihood estimation approach for several parametric models. The package also includes functions for univariate survival analysis as complementary analysis tools.

Version: 3.0
Depends: MASS, survival, Formula, R (≥ 3.3.0)
Suggests: R.rsp
Published: 2018-03-30
Author: Kyu Ha Lee, Catherine Lee, Danilo Alvares, and Sebastien Haneuse
Maintainer: Kyu Ha Lee <klee at hsph.harvard.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: Survival
CRAN checks: SemiCompRisks results

Downloads:

Reference manual: SemiCompRisks.pdf
Vignettes: This document presents a series of vignettes for the models available in SemiCompRisks package.
Package source: SemiCompRisks_3.0.tar.gz
Windows binaries: r-prerel: SemiCompRisks_3.0.zip, r-release: SemiCompRisks_3.0.zip, r-oldrel: SemiCompRisks_3.0.zip
OS X binaries: r-prerel: SemiCompRisks_3.0.tgz, r-release: SemiCompRisks_3.0.tgz
Old sources: SemiCompRisks archive

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