JM {JM} | R Documentation |
This package fits shared parameter models for the joint modelling of normal longitudinal responses and event times under a maximum likelihood approach. Various options for the survival model and optimization/integration algorithms are provided.
Package: | JM |
Type: | Package |
Version: | 0.2-2 |
Date: | 2008-12-15 |
License: | GPL |
The package has a single model-fitting function called jointModel
, which accepts as main arguments a linear
mixed effects object fit returned by function lme()
of package nlme, and a survival object fit returned
by function coxph()
or function survreg()
of package survival. In addition, the method
argument of jointModel()
specifies the type of the survival submodel to be fitted and the type of the numerical
integration technique; available options are:
"ph-GH"
"weibull-GH"
"ch-GH"
"ch-Laplace"
Dimitris Rizopoulos
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>
Henderson, R., Diggle, P. and Dobson, A. (2000) Joint modelling of longitudinal measurements and event time data. Biostatistics 1, 465–480.
Rizopoulos, D., Verbeke, G. and Lesaffre, E. (2009) Fully exponential Laplace approximation for the joint modelling of survival and longitudinal data. Journal of the Royal Statistical Society, Series B, to appear.
Tsiatis, A. and Davidian, M. (2004) Joint modeling of longitudinal and time-to-event data: an overview. Statistica Sinica 14, 809–834.
Wulfsohn, M. and Tsiatis, A. (1997) A joint model for survival and longitudinal data measured with error. Biometrics 53, 330–339.