markov_trace

Plots the Markov Trace from an object generated using <code>three_state_mm</code>

models

Markov

probabilities

transition

trace

Contains a suite of functions for survival analysis in health economics.
These can be used to run survival models under a frequentist (based on maximum likelihood)
or a Bayesian approach (both based on Integrated Nested Laplace Approximation or Hamiltonian
Monte Carlo). To run the Bayesian models, the user needs to install additional modules
(packages), i.e. 'survHEinla' and 'survHEhmc'. These can be installed from
<https://giabaio.r-universe.dev/> using
'install.packages("survHEhmc", repos = c("https://giabaio.r-universe.dev", "https://cloud.r-project.org"))'
and
'install.packages("survHEinla", repos = c("https://giabaio.r-universe.dev", "https://cloud.r-project.org"))'
respectively. 'survHEinla' is based on the package INLA, which is available for download at
<https://inla.r-inla-download.org/R/stable/>. The user can specify a set of parametric models
using a common notation and select the preferred mode of inference. The results can also be
post-processed to produce probabilistic sensitivity analysis and can be used to export the
output to an Excel file (e.g. for a Markov model, as often done by modellers and
practitioners). <doi:10.18637/jss.v095.i14>.

Gianluca Baio

survHE

Survival Analysis in Health Economic Evaluation

Andrea Berardi

Philip Cooney

Andrew Jones

Nathan Green

markov_trace function

<dl><dt>mm</dt>
<dd>The output of a call to <code>three_state_mm</code></dd>
<dt>interventions</dt>
<dd>A vector of labels for the interventions</dd>
<dt>...</dt>
<dd>additional arguments.</dd></dl>

Arguments

Author

Markov trace — markov_trace

<dl>

<dt>mm</dt>
<dd>The output of a call to <code>three_state_mm</code></dd>


<dt>interventions</dt>
<dd>A vector of labels for the interventions</dd>


<dt>...</dt>
<dd>additional arguments.</dd>

</dl>

Markov trace

markov_trace: Markov trace

Description

Usage

Value

Arguments

Author

References

See Also

Examples