summary.msm

print.summary.msm

A fitted multi-state model object, as returned by
    <code><a href="/link/msm?package=msm&version=1.2" rd-options="" data-mini-rdoc="msm::msm">msm</a></code>.

object

Vector with same elements as number of covariates
    on transition rates. Corresponds to the increase in each covariate
    used to calculate its hazard ratio. Defaults to all 1.

hazard.scale

Further arguments passed to <code><a href="/link/prevalence.msm?package=msm&version=1.2" rd-options="" data-mini-rdoc="msm::prevalence.msm">prevalence.msm</a></code>.

Summary method for fitted <code><a href="/link/msm?package=msm&version=1.2" rd-options="" data-mini-rdoc="msm::msm">msm</a></code> models. This
  is simply a wrapper around <code><a href="/link/prevalence.msm?package=msm&version=1.2" rd-options="" data-mini-rdoc="msm::prevalence.msm">prevalence.msm</a></code> which 
  produces a table of observed and
  expected state prevalences for each time, and for models with
  covariates, <code><a href="/link/hazard.msm?package=msm&version=1.2" rd-options="" data-mini-rdoc="msm::hazard.msm">hazard.msm</a></code> to print
  hazard ratios with 95% confidence intervals for covariate effects.

models

msm.summary

Functions for fitting general continuous-time Markov and
        hidden Markov multi-state models to longitudinal data.  A
        variety of observation schemes are supported, including
        processes observed at arbitrary times (panel data),
        continuously-observed processes, and censored states. Both
        Markov transition rates and the hidden Markov output process
        can be modelled in terms of covariates, which may be constant
        or piecewise-constant in time.

msm.summary: Summarise a fitted multi-state model

Description

Usage

Arguments

Value

See Also