New package: msm for multi-state models

[Chris Jackson]

Dear R users,

A new package "msm", for multi-state modelling, is now available on CRAN.  
It can be used to fit continuous-time Markov models to irregularly-observed
categorical processes.  These models are typically used for the 
progression of
chronic diseases, where a patient visits a doctor at irregular intervals 
and is
diagnosed as being in one of a set of disease stages. The transition rates
of the Markov process can be modelled as a function of covariates, and 
the models
are estimated by maximum likelihood.

The software can also fit a form of hidden Markov model: a multi-state
model in which the stages are observed with misclassification.  These 
might be
used in cases where a disease screening test is subject to false 
positives or negatives.
The probabilities of misclassification and the Markov chain transition 
rates can then
be estimated simultaneously, by maximum likelihood.  Covariates can be 
fitted to
both the transition rates and the misclassification probabilities.

Bug reports, reports of successes or failures, and suggestions for 
improvement are
welcome. We would also be interested to hear what applications people 
might be
interested in using this package for.

-- 
Christopher Jackson <chris.jackson at ic.ac.uk>, Research Associate,
Department of Epidemiology and Public Health, Imperial College School of 
Medicine, Norfolk Place, London W2 1PG


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