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Exploratory data analysis
statetable()
Summarise intermittenly-observed multi-state data
msmhist()
Illustrate the empirical distribution of states against time in intermittently-observed multistate data
msmhist_bardata()
Estimate state occupation probabilities to be illustrated by a bar plot in msmhist
msmbayes()
Bayesian multi-state models for intermittently-observed data
msmprior()
Constructor for a prior distribution in msmbayes
Getting results from fitted models
qdf()
Transition intensities from an msmbayes model, presented as a tidy data frame
qmatrix()
Transition intensity matrix from an msmbayes model
pmatrixdf()
Transition probabilities from an msmbayes model, presented as a tidy data frame
pmatrix()
Transition probability matrix from an msmbayes model
pnext()
Probabilities for the next state in a multi-state model
mean_sojourn()
Mean sojourn times from an msmbayes model
loghr()
hr()
(Log) hazard ratios for covariates on transition intensities
soj_prob()
Sojourn probability in a state of a msmbayes model
totlos()
Total length of stay in each state over an interval
loglik()
logLik(<msmbayes> )
Log likelihood from an msmbayes model
summary(<msmbayes> )
Summarise basic parameter estimates from an msmbayes model
standardise_to()
standardize_to()
Constructor for a standardising population used for model outputs
phaseapprox_pars()
Summarise posteriors for shape and scale parameters for the sojourn distribution in a semi-Markov msmbayes model
logtaf()
taf()
(Log) time acceleration factors in semi-Markov models
logoddsnext()
Summarise posteriors for log odds of transitions from phase-type states
logrrnext()
rrnext()
Effects of covariates on competing exit transitions in phase type models
edf()
Misclassification error probabilities from an msmbayes model
ematrix()
Matrix of misclassification error probabilities from an msmbayes model
Phase-type distribution utilities
msmbayes-package
The 'msmbayes' package for Bayesian multi-state modelling of intermittently-observed data