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We restricted our core sample to the preferred estimate in each study for each country or region covered, based on the author's judgement (when absent, we use the usual statistic tests).
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All results are reported utilizing weighted estimates in each study year.
The interaction effect was estimated in each study separately, then combined using a multivariate weighted average.
The interaction effect was estimated in each study separately, then combined using two different methods: a multivariate weighted average and a Bayesian random-effects model.
Two types of correlations may exist: within-study correlations, which indicate the association between outcome effect estimates in each study, and between-study correlations, which indicate how the true outcome effects are associated across studies.
Second, unmeasured or residual confounding may still affect the risk estimates in each study and thus pooled estimates in the meta-analyses, although the majority of studies tried to adjust for important confounders in the multivariable models.
The method for estimating cost in each study was assessed, extracted and categorised (Table 2).
We compute the combined RRs and 95% CIs from the estimates reported in each study.
The MAFs may be estimated separately in each study or jointly across all studies; they may also be determined from an external source.
Another explanation might be the difference in the definition of outcomes and the relative risk reduction estimates used in each study.
In the first procedure, we performed a traditional random-effects meta-analysis (ie, the frequentist approach), using the risk estimates reported in each study to characterize the overall strength of the evidence regarding the risk of PM2.5-related stroke.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com