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There are two main classes of effect size: (i) unstandardized, which are dependent from the unit of measurement; and (ii) standardized, which are independent from the evaluation criteria measurement units.
The resulting posterior MIPs are interpreted as follows: high (close to 1) for classes of effect deemed essential to the model fit, low (near 0) for those with apparently negligible effects, and in the middle (∼0.5) for those whose importance, given the data collected so far, remains uncertain (more guidelines for interpretation in Statistical Models and Methods).
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The main challenges originate from three different classes of effects.
Service quality can be divided into six broad classes of effects, summarised in Table 1, each containing different quality dimensions (as identified by [14-18] [14-18]her studies).
Three classes of effects on lineage selection may be distinguished within the proposed conceptual framework.
If long-branch effects are detected, it is necessary to discern between three classes of effects to find the best approach for an improvement of the raw data.
Reflecting the hypothesized grounding of MTT in sensory-motor processing [21], [22], [26], we therefore expect this latter class of effect to emerge during episodes of mind wandering.
The differential distributions of each class of effect (T, G, GxT and NS) between Biological Processes, Molecular Functions and Cellular Components were assessed using Fisher's exact tests, with a significance threshold of 0.05.
We term this decomposition the diallel TReVarP because it predicts based on the observed data how much each class of effect would influence drug response in a perfectly balanced, complete, future diallel.
It also allows us to estimate the portion of all variation in affinity explained by each main and epistatic effect (expressed as the increase in adjusted R when a parameter for any class of effect is added to the model) and to evaluate the statistical significance of the improvement in fit attributable to each class of parameters.
The second new test is of the class of effects DxOMark has gathered under the moniker "Depth Effects".
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