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msm (version 1.7)

Multi-State Markov and Hidden Markov Models in Continuous Time

Description

Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal data. Designed for processes observed at arbitrary times in continuous time (panel data) but some other observation schemes are supported. 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.

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Install

install.packages('msm')

Monthly Downloads

19,748

Version

1.7

License

GPL (>= 2)

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Repository

https://github.com/chjackson/msm

Maintainer

Christopher Jackson

Last Published

November 28th, 2022

Functions in msm (1.7)

Coxian phase-type distribution with two phases

Developer documentation: censoring model object

The delta method

Bootstrap resampling for multi-state models

Matrix exponential

Bronchiolitis obliterans syndrome after lung transplants

Extract model coefficients

Aortic aneurysm progression data

Calculate crude initial values for transition intensities

Heart transplant monitoring data

FEV1 measurements from lung transplant recipients

Misclassification probability matrix

Developer documentation: hidden Markov model structure object

Developer documentation: misclassification model structure object

Developer documentation: model for covariates on misclassification probabilities

Criteria for comparing two multi-state models with nested state spaces

Calculate tables of hazard ratios for covariates on transition intensities

Expected first passage time

Hidden Markov model constructors

Multivariate hidden Markov models

Extract model log-likelihood

Convert data for `msm' to data for `survival', `mstate' or `flexsurv' analysis

msm.form.qoutput

Extract msm model parameter estimates in compact format

Fitted msm model objects

Measurement error distributions

model.frame.msm

Extract original data from msm objects.

Multi-state Markov and hidden Markov models in continuous time

paramdata.object

Developer documentation: internal msm parameters object

Likelihood ratio test

Calculate tables of odds ratios for covariates on misclassification probabilities

pmatrix.piecewise.msm

Transition probability matrix for processes with piecewise-constant intensities

plot.prevalence.msm

Plot of observed and expected prevalences

Probability of each state being next

Transition probability matrix

Plots of multi-state models

Kaplan Meier estimates of incidence

Pearson-type goodness-of-fit test

Parameters of phase-type models in mixture form

Exponential distribution with piecewise-constant rate

plot.survfit.msm

Plot empirical and fitted survival curves

Passage probabilities

Developer documentation: model for covariates on transition intensities

Developer documentation: transition model structure object

Transition intensity matrix

Print a fitted msm model object

Estimated ratio of transition intensities

Print a fitted msm model object

Tables of observed and expected prevalences

Generic function to find quantiles of a distribution

Psoriatic arthritis data

recreate.olddata

Convert data stored in msm object to old format

Truncated Normal distribution

Simulate one individual trajectory from a continuous-time Markov model

Table of transitions

Explore the likelihood surface

Simulate from a Markov model fitted using msm

Mean sojourn times from a multi-state model

Simulate multiple trajectories from a multi-state Markov model with arbitrary observation times

Calculate the probabilities of underlying states and the most likely path through them

Summarise a fitted multi-state model

Total length of stay, or expected number of visits

Score residuals

Transient and absorbing states