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In the first method, we calculated residuals from a regression between brain and body mass and used these in a subsequent regression analysis with root-to-tip ω.
The HHT decomposition results were further used as the input data for a subsequent regression analysis to investigate the association between excess mortality and different risk factors such as temperature, ozone, and particulate matter.
Propensity scores were then used in a subsequent regression model as a regressor along with the primary predictors (fluids and vasoactive agents), while the outcome variable was inhospital mortality.
To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors.
Once the original time series is decomposed into trend and non-trend IMFs, calculation of the excess mortality or other data analysis procedures (e.g., a subsequent regression analysis) can be performed using the resulting IMFs as the input.
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The same was determined for all subsequent regression analyses.
This reaction phenomenon may give the illusion of a spike and subsequent regression.
The choice of a 3-point scale was made to facilitate interpretation of the subsequent regression analysis and to ensure an adequate number of responses in each category.
This scheme firstly develops a fixed region model to select the best set of predictor variables for use in the subsequent regression analyses using an approach that minimises the model error variance while also satisfying a number of statistical selection criteria.
Therefore, these variables were entered in the first step of the subsequent regression analysis, yielding an explained variance of 13% (see Table 4).
In subsequent regression analyses, 'slope' is a bivariate variable with two values corresponding to either no slope or a slope of 0.5 and a northeast aspect.
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