summary.survHE

Calculates the mean survival time as the area under the survival curve

models

survival

mean

time

Parametric

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

summary.survHE function

<dl><dt>object</dt>
<dd>a <code>survHE</code> object (resulting from the call to
<code>fit.models</code></dd>
<dt>mod</dt>
<dd>the model to be analysed (default = 1)</dd>
<dt>t</dt>
<dd>the vector of times to be used in the computation. Default = NULL,
which means the observed times will be used. NB: the vector of times should
be: i) long enough so that S(t) goes to 0; and ii) dense enough so that the
approximation to the AUC is sufficiently precise</dd>
<dt>nsim</dt>
<dd>the number of simulations from the survival curve distributions
to be used (to compute interval estimates)</dd>
<dt>...</dt>
<dd>Additional options</dd></dl>

Arguments

Author

Prints a summary table for the distribution the mean survival time for a
given model and data — summary.survHE

<dl>

<dt>object</dt>
<dd>a <code>survHE</code> object (resulting from the call to
<code>fit.models</code></dd>


<dt>mod</dt>
<dd>the model to be analysed (default = 1)</dd>


<dt>t</dt>
<dd>the vector of times to be used in the computation. Default = NULL,
which means the observed times will be used. NB: the vector of times should
be: i) long enough so that S(t) goes to 0; and ii) dense enough so that the
approximation to the AUC is sufficiently precise</dd>


<dt>nsim</dt>
<dd>the number of simulations from the survival curve distributions
to be used (to compute interval estimates)</dd>


<dt>...</dt>
<dd>Additional options</dd>

</dl>

Prints a summary table for the distribution the mean survival time for a
given model and data

summary.survHE: Prints a summary table for the distribution the mean survival time for a given model and data

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples