netmeta (version 0.4-0)

decomp.design: Design-based decomposition of Cochran's Q in network meta-analysis

Description

This function performs a design-based decomposition of Cochran's Q for assessing the homogeneity in the whole network, the homogeneity within designs, and the homogeneity/consistency between designs. It allows also an assessment of the consistency assumption after detaching the effect of single designs.

Usage

decomp.design(x)

Arguments

x

An object of class netmeta.

Value

• A list containing the following components:
• Q.decomp
  Data frame with Q statistics (variable Q) to assess the homogeneity/consistency in the whole network, within designs, and between designs. Corresponding degrees of freedom (df) and p-values (pval) are also given.
• Q.design
  Data frame with design-specific decomposition of the within-designs Q statistic (Q), corresponding degrees of freedom (df) and p-values (pval) as well as information on the designs (design) are given.
• Q.detach
  Data frame with between-designs Q statistics (Q) after detaching of single designs, corresponding degrees of freedom (df) and p-values (pval) as well as information on the detached design (design) are given.
• residuals
  Matrix with residuals.
• Q.inc.design
  A named vector with contribution of single designs to the between design Q statistic.
• call
  Function call.
• version
  Version of R package netmeta used to create object.

Details

In the context of network meta-analysis and the assessment of the homogeneity and consistency assumption, a generalized Cochran's Q statistic for multivariate meta-analysis can be used as shown in Krahn et al. (2013). This Q statistic can be decomposed in a sum of within-design Q statistics and one between-designs Q statistic that incorporates the concept of design inconsistency, see Higgins et al. (2012).

Since an inconsistent treatment effect of one design can simultaneously inflate several residuals, Krahn et al. (2013) suggest for locating the inconsistency in a network to fit a set of extended models allowing for example for a deviating effect of each study design in turn. The recalculated between-designs Q statistics are given in list component Q.detach. The change of the inconsistency contribution of single designs can be investigated in more detail by a net heat plot (see function netheat). Designs where only one treatment is involved in other designs of the network or where the removal of corresponding studies would lead to a splitting of the network do not contribute to the inconsistency assessment. These designs are not included in Q.detach.

References

Higgins JPT, Jackson D, Barrett JK, Lu G, Ades AE, White IR (2012), Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies. Research Synthesis Methods, 3(2), 98--110.

Krahn U, Binder H, König J (2013), A graphical tool for locating inconsistency in network meta-analyses. BMC Medical Research Methodology, 13, 35.

See Also

netmeta, netheat

Examples

##
## Note: Contrary to these data, in Krahn et al. (2013) slightly
## different standard errors related to individual studies are used
## calculated by the function 'metacont' of R package 'meta'.
##
data(Senn2013)

##
## Generation of an object of class 'netmeta' with
## reference treatment 'plac', i.e. placebo
##
net1 <- netmeta(TE, seTE, treat1, treat2, studlab,
                data=Senn2013, sm="MD", reference="plac")

##
## Decomposition of Cochran's Q 
##
decomp.design(net1)