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Where data allowed, effect sizes were computed for each study and random-effects inverse-variance weighted meta-analytic methods were used to synthesise the evidence.
The effect sizes were computed for each participating country for each survey, and then averaged across countries (each country being equal to one).
Additionally, effect sizes were computed for all mean differences using Cohen's d measure (Cohen, 1988) to demonstrate the magnitude of each difference.
After all reads were assigned, maximum contig sizes were computed for each genome, normalized to read lengths, and the minimum of these (referred to here as the minimax contig size) was recorded.
η effect sizes were computed for regression models.
Moreover, median effect sizes were computed for each factor and presented in the Tables.
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Cohen's d statistic for effect sizes was computed for individual contrasts [39].
Two measures of effect size were computed for group comparisons on neurocognitive and ToM variables: Cohen's d, and the explanatory measure of effect size ξ (xi) proposed by Wilcox and Tian (2011).
PVHS configurations with the same PV array size were computed for varying energy demand (D1) and constant daily energy demand (D2) when the minimum desired renewable energy fraction was set to 20%.
Regressions of Procrustes coordinates against the logarithm of centroid size were computed for all families (except for all mono-specific families), yielding family-specific allometric shape vectors (ASVf).
An even more trivial effect size was computed for the wholist-verbalisers and analytic-imagers (d = 0.02 and d = 0.01 respectively).
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