The statistical importance of a study for a network meta-analysis estimate.

Rücker, Gerta; Nikolakopoulou, Adriani; Papakonstantinou, Theodoros; Salanti, Georgia; Riley, Richard D; Schwarzer, Guido (2020). The statistical importance of a study for a network meta-analysis estimate. BMC Medical research methodology, 20(1), p. 190. BioMed Central 10.1186/s12874-020-01075-y

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BACKGROUND

In pairwise meta-analysis, the contribution of each study to the pooled estimate is given by its weight, which is based on the inverse variance of the estimate from that study. For network meta-analysis (NMA), the contribution of direct (and indirect) evidence is easily obtained from the diagonal elements of a hat matrix. It is, however, not fully clear how to generalize this to the percentage contribution of each study to a NMA estimate.

METHODS

We define the importance of each study for a NMA estimate by the reduction of the estimate's variance when adding the given study to the others. An equivalent interpretation is the relative loss in precision when the study is left out. Importances are values between 0 and 1. An importance of 1 means that the study is an essential link of the pathway in the network connecting one of the treatments with another.

RESULTS

Importances can be defined for two-stage and one-stage NMA. These numbers in general do not add to one and thus cannot be interpreted as 'percentage contributions'. After briefly discussing other available approaches, we question whether it is possible to obtain unique percentage contributions for NMA.

CONCLUSIONS

Importances generalize the concept of weights in pairwise meta-analysis in a natural way. Moreover, they are uniquely defined, easily calculated, and have an intuitive interpretation. We give some real examples for illustration.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)

UniBE Contributor:

Nikolakopoulou, Adriani, Papakonstantinou, Theodoros, Salanti, Georgia

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

1471-2288

Publisher:

BioMed Central

Funders:

[4] Swiss National Science Foundation

Language:

English

Submitter:

Andrea Flükiger-Flückiger

Date Deposited:

22 Jul 2020 20:06

Last Modified:

05 Dec 2022 15:39

Publisher DOI:

10.1186/s12874-020-01075-y

PubMed ID:

32664867

Uncontrolled Keywords:

Network meta-analysis Study contribution Study importance Study weight

BORIS DOI:

10.7892/boris.145294

URI:

https://boris.unibe.ch/id/eprint/145294

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