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Changes for each measure were assessed by linear mixed model with repeated measures adjusted for confounding variables.
Throughout the study, we used statistical measures adjusted for multiple testing.
Table 4 shows the corresponding results for neighbourhood deprivation and density measures, adjusted for all individual level variables.
Multiple variable logistic and linear regression models examining the associations between key measures, adjusted for confounders identified a priori.
When reports contained multivariate analyses, we prioritised simple effects; however if no simple effects were reported, we included outcome measures adjusted for other variables.
Table 3 shows the effect of school deprivation and ethnic density measures, adjusted for all individual-level variables, on psychological well-being.
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Biochemical markers were compared using mixed regression models to take account of the repeated measures, adjusting for preoperative measurements of the markers and participating centre.
These measures adjust for unequal sample sizes.
ANCOVA analyses were used to compare differences between groups on 25-OHD and functional measures, adjusting for relevant variables.
Utilities were modelled using linear mixed effects models for repeated measures adjusting for baseline and for whether the observed utility occurred preprogression or postprogression.
We estimated models for each marker of lead exposure as well as for bone lead measures adjusting for blood lead concentrations.
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