Table 2.

Scenarios for the simulation set-up

Number of trials per comparison
typical loop	NO = 1, NP = 3,  OP = 4
Trial size ($n_{i,k}^E=n_{i,k}^C=n_i$ in trial i)
<  50 (small)	ni~U(12, 39) placebo-controlled trials
	ni~U(15, 49) old-controlled trials
>  100 (moderate)	ni~U(102, 187) placebo-controlled trials ni~U(128, 241) old-controlled trials
Initial event rates of the control arm in trial  i
low events	$p_{i,P}^{C,0}~U\left(0.05,0.09\right)$ placebo-controlled trials
	$p_{i,O}^{C,0}~U\left(0.10,0.15\right)$ old-controlled trials
frequent events	$p_{i,P}^{C,0}~U\left(0.27,0.40\right)$ placebo-controlled trials
	$p_{i,O}^{C,0}~U\left(0.63,0.76\right)$ old-controlled trials
Unbalanced risk of missing outcome data ($q_{i,k}^E<q_{i,k}^C$ in trial i)
moderate	$q_{i,k}^E~U\left(0.05,0.10\right)$, $q_{i,k}^C~U\left(0.11,0.20\right)$
large	$q_{i,k}^E~U\left(0.21,0.30\right)$, $q_{i,k}^C~U\left(0.31,0.40\right)$
Missingness mechanisms via log IMOR
informative	φi, P~TN(μ =  −  log (2), σ2 = 1, a =  log (1))
	φi, k~TN(μ =  log (2), σ2 = 1, a =  log (1)) k = N, O
Treatment effects
basic parameters	LORNP =  ln (2), LOROP =  ln (1.5)
functional parameter	LORNO = LORNP − LOROP (consistency equation)
Common between-trial variance
predictive distribution	τ2~LΝ(−3.95, 1.342) (small) τ2~LΝ(−2.56, 1.742) (substantial)

Note: C Control; E Experimental arm; IMOR Informative missingness odds ratio; LN Log-normal distribution; LOR Log odds ratio; N New intervention; O Old intervention; P Placebo; T Truncated normal distribution; U Uniform distribution

Typical loop as defined by Veroniki et al. [32]

Using predictive log-normal distributions that correspond to all-cause mortality and generic health setting for small and substantial between-trial variance, respectively [33]