netconnection.crossnma {crossnma}

Get information on network connectivity (number of subnetworks, distance matrix)

Description

To determine the network structure and to test whether a given network is fully connected. The function calculates the number of subnetworks (connectivity components; value of 1 corresponds to a fully connected network) and the distance matrix (in block-diagonal form in the case of subnetworks). If some treatments are combinations of

Usage

## S3 method for class 'crossnma'
netconnection(data, ...)

Arguments

data

An object produced by crossnma.

...

... Additional arguments (passed on to netconnection)

Value

An object of class netconnection with corresponding print function. The object is a list containing the following components:

treat1, treat2, studlab, title, warn, nchar.trts

As defined above.

k

Total number of studies.

m

Total number of pairwise comparisons.

n

Total number of treatments.

n.subnets

Number of subnetworks; equal to 1 for a fully connected network.

D.matrix

Distance matrix.

A.matrix

Adjacency matrix.

L.matrix

Laplace matrix.

call

Function call.

version

Version of R package netmeta used to create object.

Author(s)

Guido Schwarzer [e-mail]

See Also

netconnection

Examples

## Not run: 
# We conduct a network meta-analysis assuming a random-effects
# model.
# The data comes from randomized-controlled trials and
# non-randomized studies (combined naively)
head(ipddata) # participant-level data
stddata # study-level data

# Create a JAGS model
mod <- crossnma.model(treat, id, relapse, n, design,
  prt.data = ipddata, std.data = stddata,
  reference = "A", trt.effect = "random", method.bias = "naive")

# Fit JAGS model
set.seed(1909)
fit <- crossnma(mod)

# Check network connectivity
netconnection(fit)

## End(Not run)