p3state.msm-package: Analyzing survival data from an illness-death model

In p3state.msm: Analyzing Survival Data from an Illness-Death Model

Analyzing survival data from an illness-death model

Description

p3state.msm provides functions for estimating semi-parametric regression models but also to implement nonparametric estimators for the transition probabilities. The methods can also be used in progressive three-state models. In progressive three-state models, estimators for other quantities such as the bivariate distribution function (for the sequentially ordered events) are also given.

Details

Package:	p3state.msm
Type:	Package
Version:	1.3.2
Date:	2023-01-19
License:	GPL-3
LazyLoad:	yes
LazyData:	yes

Author(s)

Luis Meira-Machado, Javier Roca Pardinas [e-mail]
and Artur Araújo [e-mail]
Maintainer: Luis Meira-Machado [e-mail]

References

Crowley J., Hu M. (1977). Covariance analysis of heart transplant survival data. Journal of the American Statistical Association, 72(357), 27-36. doi: 10.2307/2286902

Meira-Machado L., De Una-Alvarez J., Cadarso-Suarez C. (2006). Nonparametric estimation of transition probabilities in a non-Markov illness-death model. Lifetime Data Analysis, 12(3), 325-344. doi: 10.1007/s10985-006-9009-x

de Una-Alvarez J., Meira-Machado L. (2008). A simple estimator of the bivariate distribution function for censored gap times. Statistics & Probability Letters, 78(15), 2440-2445. doi: 10.1016/j.spl.2008.02.031

Meira-Machado L., Roca-Pardinas J. (2011). p3state.msm: Analyzing Survival Data from an Illness-Death Model. Journal of Statistical Software, 38(3), 1-18. doi: 10.18637/jss.v038.i03

p3state.msm documentation built on Jan. 22, 2023, 1:34 a.m.