Generating Multi-State Survival Data

Description

The genSurv software permits to generate data wih one binary time-dependent covariate and data stemming from a progressive illness-death model.

Details

Package: genSurv
Type: Package
Version: 1.0.3
Date: 2015-11-09
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes

Author(s)

Artur Araújo, Luís Meira-Machado lmachado@math.uminho.pt
and Susana Faria sfaria@math.uminho.pt
Maintainer: Artur Araújo artur.stat@gmail.com

References

Anderson, P. K., Gill, R. D. (1982) Cox's regression model for counting processes: a large sample study. Annals of Statistics, 10:1100-1120.

Cox, D.R. (1972). Regression models and life tables (with discussion). Journal of the Royal Statistical Society, Series B 34:187-220.

Jackson, C. (2007). Multi-state modelling with R: the msm package, Cambridge, U.K.

Johnson, M. E. (1987). Multivariate Statistical Simulation, John Wiley and Sons.

Johnson, N., Kotz, S. (1972). Distribution in statistics: continuous multivariate distributions, John Wiley and Sons.

Lu J., Bhattacharya, G. (1990). Some new constructions of bivariate weibull models, Annals of Institute of Statistical Mathematics, 42:543-559.

Meira-Machado, L., Cadarso-Suárez, C., De Uña- Álvarez, J., Andersen, P.K. (2009). Multi-state models for the analysis of time to event data. Statistical Methods in Medical Research 18(2):195-222.

Meira-Machado, L., Roca-Pardiñas, J. (2011). p3state.msm: Analyzing Survival Data from an Illness-Death Model. Journal of Statistical Software, 38(3): 1-18.

Therneau, T.M., Grambsch, P.M. (2000). Modelling survival data: Extending the Cox Model. New York: Springer.