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To cope with this, specialized software such as MANTRA, which allows effect size to vary across different populations, has been developed [ 42].
This allows effect size (η k) for the kth latent variable to be estimated as the ratio of the square of the singular value associated with that particular latent variable to the sum of all squared singular values derived from the decomposition.
In order to compare the effect sizes of variables in the five different areas under investigation for associations with SRHS (see above), partial Eta-square statistic was used as it allows effect sizes to be compared across different variables, independent of any other variables included in the model [ 34, 35].
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The higher-end model EX-Z300 also has a "Makeup button" that allows effects to be applied with one touch.
This coding format allows effects to be separated from the overall mean effects measured in the utility function [22,53].
In applying the Inhomogeneous MUSIG approach, a deeper understanding of the flow structures is possible and the model allows effects of polydispersion to be investigated.
The large volume allows effects to be estimated with great precision, i.e. narrow confidence intervals, so even small effects are regarded as highly statistically significant.
The final worksheets present results and allow effect data to be entered and cost-effectiveness results to be calculated.
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.
Pollutants with IQR/median ratios ≤0.30 were excluded, as they were not sufficiently variable to allow effect estimation with sufficient power [ 24].
In this landscape, sheep grazing is constrained by access to water, allowing effects to be examined independent of topography and vegetation community.
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