summary.missingHE

Produces a table printout with some summary results of the health economic evaluation probabilistic model
run using the function <code>selection</code>, <code>selection_long</code>, <code>pattern</code> or <code>hurdle</code>.

Contains a suite of functions for health economic evaluations with missing outcome data.
The package can fit different types of statistical models under a fully Bayesian approach using the software 'JAGS' (which should be installed locally and which is loaded in 'missingHE' via the 'R' package 'R2jags').
Three classes of models can be fitted under a variety of missing data assumptions: selection models, pattern mixture models and hurdle models.
In addition to model fitting, 'missingHE' provides a set of specialised functions to assess model convergence and fit, and to summarise the statistical and economic results using different types of measures and graphs.
The methods implemented are described in Mason (2018) <doi:10.1002/hec.3793>, Molenberghs (2000) <doi:10.1007/978-1-4419-0300-6_18> and Gabrio (2019) <doi:10.1002/sim.8045>.

Andrea Gabrio

missingHE

Missing Outcome Data in Health Economic Evaluation

summary.missingHE function

<dl><dt>object</dt>
<dd>A <code>missingHE</code> object containing the results of the Bayesian modelling and the economic evaluation</dd>
<dt>...</dt>
<dd>Additional arguments affecting the summary produced.</dd></dl>

Arguments

Author

Summary method for objects in the class missingHE — summary.missingHE

<dl>

<dt>object</dt>
<dd>A <code>missingHE</code> object containing the results of the Bayesian modelling and the economic evaluation</dd>


<dt>...</dt>
<dd>Additional arguments affecting the summary produced.</dd>

</dl>

summary.missingHE: Summary method for objects in the class `missingHE`

Description

Usage

Value

Arguments

Author

References

See Also

Examples