Multi-state models are models for a process, for example describing a life history of an
individual, which at any time occupies one of a few possible states. This can describe …

Survival data or more general time-to-event data occur in many areas, including medicine,
biology, engineering, economics, and demography, but previously standard methods have …

The experience of a patient in a survival study may be modelled as a process with two states
and one possible transition from an “alive” state to a “dead” state. In some studies, however …

The multi-state Markov model is a useful way of describing a process in which an individual
moves through a series of states in continuous time. The msm package for R allows a …

Multistate Models for the Analysis of Life History Data provides the first comprehensive
treatment of multistate modeling and analysis, including parametric, nonparametric and …

Data related to life histories of individuals can be obtained in many different ways, and the
usefulness of multi‐state models for statistical analysis is generally highly dependent on the …

Standard survival data measure the time span from some time origin until the occurrence of
one type of event. If several types of events occur, a model describing progression to each of …

I first discuss the main assumptions which can be made for multi-state models: the time-
homogeneity and semi-Markov assumptions, the problem of choice of the time scale, the …

An introduction to event history analysis via multi-state models is given. Examples include
the two-state model for survival analysis, the competing risks and illness-death models, and …

Multistate models are increasingly being used to model complex disease profiles. By
modelling transitions between disease states, accounting for competing events at each …