Description Usage Arguments Details Value Author(s) See Also

Extract the estimated transition intensity matrix, and the corresponding standard errors, from a fitted multi-state model at a given set of covariate values.

1 2 3 | ```
qmatrix.msm(x, covariates="mean", sojourn=FALSE,
ci=c("delta","normal","bootstrap","none"), cl=0.95,
B=1000, cores=NULL)
``` |

`x` |
A fitted multi-state model, as returned by |

`covariates` |
The covariate values at which to estimate the intensity matrix.
This can either be: the string the number or a list of values, with optional names. For example
where the order of the list follows the order of the covariates originally given in the model formula. Or more clearly, a named list,
If some covariates are specified but not others, the missing ones default to zero. With |

`sojourn` |
Set to TRUE if the estimated sojourn times and their standard errors should also be returned. |

`ci` |
If If If |

`cl` |
Width of the symmetric confidence interval to present. Defaults to 0.95. |

`B` |
Number of bootstrap replicates, or number of normal simulations from the distribution of the MLEs. |

`cores` |
Number of cores to use for bootstrapping using parallel
processing. See |

Transition intensities and covariate effects are estimated on the log
scale by `msm`

. A covariance matrix is estimated from the
Hessian of the maximised log-likelihood.

A more practically meaningful parameterisation of a continuous-time Markov model
with transition intensities *q_{rs}* is in terms of the mean
sojourn times *-1 / q_{rr}* in each state *r* and the
probabilities that the next move of the process when in state *r*
is to state *s*, *-q_{rs} / q_{rr}*.

A list with components:

`estimate` |
Estimated transition intensity matrix. |

`SE` |
Corresponding approximate standard errors. |

`L` |
Lower confidence limits |

`U` |
Upper confidence limits |

Or if `ci="none"`

, then `qmatrix.msm`

just returns the
estimated transition intensity matrix.

If `sojourn`

is `TRUE`

, extra components called
`sojourn`

, `sojournSE`

, `sojournL`

and `sojournU`

are included, containing the
estimates, standard errors and confidence limits, respectively, of the
mean sojourn times in each transient state.

The default print method for objects returned by
`qmatrix.msm`

presents estimates and confidence limits. To
present estimates and standard errors, do something like

`qmatrix.msm(x)[c("estimates","SE")]`

C. H. Jackson [email protected]

`pmatrix.msm`

, `sojourn.msm`

,
`deltamethod`

, `ematrix.msm`

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