Identify comparisons in loops that fulfil criteria for node-splitting
inconsistency.loops.Rd
Identify comparisons informed by both direct and indirect evidence from independent sources, which therefore fulfil the criteria for testing for inconsistency via node-splitting. Follows the method of van Valkenhoef van Valkenhoef et al. (2016) .
Arguments
- data
A data frame containing variables
studyID
andtreatment
(as numeric codes) that indicate which treatments are used in which studies.
Value
A data frame of comparisons that are informed by direct and indirect
evidence from independent sources. Each row of the data frame is a
different treatment comparison. Numerical codes in t1
and t2
correspond
to treatment codes.
Details
Similar to gemtc::mtc.nodesplit()
but uses a fixed
reference treatment and therefore suggests fewer loops in which to test for
inconsistency. Heterogeneity can also be parameterised as inconsistency and
so testing for inconsistency in additional loops whilst changing the
reference treatment would also be identifying heterogeneity. Depends on igraph
.
References
van Valkenhoef G, Dias S, Ades AE, Welton NJ (2016). “Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis.” Res Synth Methods, 7(1), 80-93. ISSN 1759-2887 (Electronic) 1759-2879 (Linking), doi:10.1002/jrsm.1167 , https://pubmed.ncbi.nlm.nih.gov/26461181/.
Examples
data <- data.frame(studyID=c(1,1,2,2,3,3,4,4,5,5,5),
treatment=c(1,2,1,3,2,3,3,4,1,2,4)
)
# Identify comparisons informed by direct and indirect evidence
inconsistency.loops(data)
#> t1 t2 path
#> 5 3 4 3->1->4
#> 4 2 3 2->1->3