Table 1 List of the parameters explored through simulation with descriptions

Number of nodes (treatments) in the network

3

The number of nodes speaks directly to the principal objective of whether too few IPD data will have an affect the estimated treatment-effects in a noticeable manner. More nodes means more data are required for full coverage.

5

10

Proportion of treatment comparisons with IPD

Low

Low implied only a single treatment comparison with IPD. Medium implied multiple edges with IPD, but among the lower number of multiple edges possible for the given network. High allowed for up to 100% of edges having IPD

Medium

High

Effect-modification

None

The relationship between the covariate X and the relative treatment-effects. None indicates no relationship (treatment-effects are unchanged by varying values of the covariate). Constant indicates that the linear relationship between the covariate treatment-effect has the same slope for all treatment-effects relative to the reference treatment. Exchangeable indicates that the slope between covariate and treatment-effect changes according to the treatments being compared, but that they come from a common distribution of slopes. (see Fig. 1)

Constant

Exchangeable

Trial sizes

All trials of equal sizes

All trials had 200 patients per arm when set to equal. When IPD were larger, the IPD trials had 500 patients per arm. All trials were 2-arm trials.

IPD trials are bigger

Network density

Sparse

Sparse networks were star networks with no closed loops. They had 1–3 trials per treatment comparison. Well-populated trials had closed loops and treatment comparisons with up to 7 trials.

Well-populated