netconnection.crossnma function

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

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

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

Arguments

• data: An object produced by crossnma.
• ...: ... Additional arguments (passed on to netconnection).

Returns

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.

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)

See Also

netconnection

Author(s)

Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de