waic

Compute log pointwise predictive density, effective number of parameters and WAIC.

internal

Modelling of sensitivity and specificity on their natural scale
using copula based bivariate beta-binomial distribution to yield marginal
mean sensitivity and specificity. The intrinsic negative correlation between
sensitivity and specificity is modelled using a copula function. A forest plot
can be obtained for categorical covariates or for the model with intercept only.
Nyaga VN, Arbyn M, Aerts M (2017) <doi:10.18637/jss.v082.c01>.

Victoria N Nyaga

CopulaDTA

Copula Based Bivariate Beta-Binomial Model for Diagnostic Test
Accuracy Studies

waic function

<dl><dt>model</dt>
<dd>stanfit object</dd></dl>

Arguments

Author

Compute log pointwise predictive density, effective number of parameters and WAIC. — waic

<dl>

<dt>model</dt>
<dd>stanfit object</dd>

</dl>

waic: Compute log pointwise predictive density, effective number of parameters and WAIC.

Description

Usage

Arguments

Author