calculate.deviance {bnma} | R Documentation |

## Find deviance statistics such as DIC and pD.

### Description

Calculates deviance statistics. This function automatically called in `network.run`

and the deviance statistics are stored after sampling is finished.

### Usage

```
calculate.deviance(result)
```

### Arguments

`result` |
Object created by |

### Value

`Dbar` |
Overall residual deviance |

`pD` |
Sum of leverage_arm (i.e. total leverage) |

`DIC` |
Deviance information criteria (sum of Dbar and pD) |

`data.points` |
Total number of arms in the meta analysis |

`dev_arm` |
Posterior mean of the residual deviance in each trial arm |

`devtilda_arm` |
Deviance at the posterior mean of the fitted values |

`leverage_arm` |
Difference between dev_arm and devtilda_arm for each trial |

`rtilda_arm` |
Posterior mean of the fitted value for binomial and multinomial |

`ybar_arm` |
Posterior mean of the fitted value for normal |

### References

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. doi:10.1177/0272989X12458724

### Examples

```
#parkinsons
network <- with(parkinsons, {
network.data(Outcomes, Study, Treat, SE = SE, response = "normal")
})
result <- network.run(network)
calculate.deviance(result)
```

*bnma*version 1.6.0 Index]