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This technique eases interpretation of the parameter estimates related to BCS.
We find SOM to be an attractive framework for developing ambient air quality classification because the approach eases interpretation of results by allowing users to visualize classifications on an organized map.
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We divide them in three categories to ease interpretation.
Furthermore, in our regressions, we chose not to include interactions aiming at easing interpretation of results.
We fit a second-order CFA model to ease interpretation of the scale and increase parsimony.
Power BI is an influential analytical tool offering a friendly interface, whereby interactive visualization can be easily created to ease interpretation and do efficient reporting.
To improve model fit, outcome variables were natural log transformed and then the regression coefficients were back transformed to original scale to ease interpretation.
To ease interpretation, data is generally presented as the cumulative amount in the entire GIT, e.g. the sum of the four sections in each animal.
To ease interpretation, all regressors are centred around their sample averages, so that π1 can be interpreted as the average unexplained gender pay gap in the full sample.
Continuous predictors were mean-centered to reduce multicollinearity and to ease interpretation of interaction terms.
For ease interpretation, incidence rate ratios (IRR) were reported.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com