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Heterogeneity of effect measures in intervention studies undermines the use of evidence to inform policy.
Table 6 Results of the robustness test for systematic differences in the heterogeneity of effect sizes Hypothesis Taxes (H1) Bankruptcy and financial distress costs (H2) Dep.
There was substantial heterogeneity of effect among the four sub-cohorts (; I-squared inconsistency 90.3%, p<0.001).
There was no statistical evidence of heterogeneity of effect across anoscopists for either sensitivity or specificity (I-squared p-values 0.136 and 0.237, respectively).
The heterogeneity of effect sizes in meta-analyses also appears to be similar in the physical and the social sciences, suggesting a similar level of empirical cumulativeness [22].
We explored possible heterogeneity of effect by serogroup or case occurrence during influenza season (November through April) versus non-influenza season using stratum-specific analyses, with heterogeneity of effects across strata assessed using the meta-analytic Q-statistic [24].
Because the four sub-cohorts differed according to inclusion criterion, clinical setting, screening-question expression, and assay methodology, we analyzed each separately and then pooled across subcohorts after examining heterogeneity of effect.
Heterogeneity of effect sizes was evaluated by the I2 statistic.
There is a great heterogeneity of effect sizes.
No heterogeneity of effect estimates on relative risks was observed (P=0.46, I=0%).
An important question is what the explanation is for the observed heterogeneity of effect estimates.
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