calculate.contrast.deviance: Find deviance statistics such as DIC and pD.

In bnma: Bayesian Network Meta-Analysis using 'JAGS'

Find deviance statistics such as DIC and pD.

Description

Calculates deviance statistics. This function automatically called in contrast.network.run and the deviance statistics are stored after sampling is finished.

Usage

calculate.contrast.deviance(result)

Arguments

result

Object created by contrast.network.run function

Value

Dbar	Overall residual deviance
pD	Sum of leverage_arm (i.e. total leverage)
DIC	Deviance information criteria (sum of Dbar and pD)
resdev_study	Posterior mean of the residual deviance in each study
devtilda_study	Deviance at the posterior mean of the fitted values
leverage_study	Difference between resdev_study and devtilda_study for each trial

References

A.J. Franchini, S. Dias, A.E. Ades, J.P. Jansen, N.J. Welton (2012), Accounting for correlation in network meta-analysis with multi-arm trials, Research Synthesis Methods 3(2):142-160. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/jrsm.1049")}

S. Dias, A.J. Sutton, A.E. Ades, and N.J. Welton (2013a), A Generalized Linear Modeling Framework for Pairwise and Network Meta-analysis of Randomized Controlled Trials, Medical Decision Making 33(5):607-617. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0272989X12458724")}

Examples

network <- with(parkinsons_contrast, {
 contrast.network.data(Outcomes, Treat, SE, na, V)
})

result <- contrast.network.run(network)
calculate.contrast.deviance(result)

bnma documentation built on May 29, 2024, 11:53 a.m.