Table 4.

Abbreviations used for analysis models

NN-DL	Normal-normal (NN) model using the DerSimonian-Laird (DL) heterogeneinty estimator
NN-REML	NN model using the restricted maximum-likelihood (REML) estimator
NN-EB	NN model using the empirical-Bayes (EB) estimator
PN-PL	Poisson model using profile likelihood (PL) estimation
BN-UM.FS	Binomial model using unconditional logistic regression and fixed study (nuisance) parameters
BN-UM.RS	Binomial model using unconditional logistic regression and random study (nuisance) parameters
BN-CM.EL	Conditional (hypergeometric) model (exact likelihood)
BN-CM.AL	Conditional (hypergeometric) model (approximate likelihood)
NN-Bayes HN(0.5)	NN Bayesian model using a half-normal heterogeneity prior with scale 0.5
NN-Bayes HN(1.0)	NN Bayesian model using a half-normal heterogeneity prior with scale 1.0