loo.disbayes

Leave-one-out cross validation for disbayes models

Estimation of incidence and case fatality for a chronic disease, given partial information, using a multi-state model. Given data on age-specific mortality and either incidence or prevalence, Bayesian inference is used to estimate the posterior distributions of incidence, case fatality, and functions of these such as prevalence. The methods are described in Jackson et al. (2023) <doi:10.1093/jrsssa/qnac015>.

Christopher Jackson

disbayes

Bayesian Multi-State Modelling of Chronic Disease Burden Data

loo.disbayes function

<dl><dt>x</dt>
<dd>A model fitted by <code>disbayes</code>. Any of the computation methods
are supported.</dd>
<dt>outcome</dt>
<dd>Either <code>"overall"</code>, to assess the fit to all data, or 
one of <code>"inc"</code>, <code>"prev"</code>, <code>"mort"</code> or <code>"rem"</code>, to assess the fit
to the incidence data, prevalence data, mortalidy data or remission data, respectively.</dd>
<dt>...</dt>
<dd>Other arguments (currently unused).</dd></dl>

Arguments

Leave-one-out cross validation for disbayes models — loo.disbayes

<dl>

<dt>x</dt>
<dd>A model fitted by <code>disbayes</code>. Any of the computation methods
are supported.</dd>


<dt>outcome</dt>
<dd>Either <code>"overall"</code>, to assess the fit to all data, or 
one of <code>"inc"</code>, <code>"prev"</code>, <code>"mort"</code> or <code>"rem"</code>, to assess the fit
to the incidence data, prevalence data, mortalidy data or remission data, respectively.</dd>


<dt>...</dt>
<dd>Other arguments (currently unused).</dd>

</dl>

loo.disbayes: Leave-one-out cross validation for disbayes models

Description

Usage

Value

Arguments

See Also