In our study, we interpret the variability observed at 5 dpf not as a sign of dilution of maternal protein but of morpholinos instead.
Once we classify the areas, we can interpret the variability by looking at the time profiles of the estimated interactions.
To interpret the variability shown in the squares classified as "unstable," it is useful to attempt to cluster the time profiles of the interactions.
Conversely, clustering combinations that produce a small number of clusters, e.g., two, are difficult to interpret because the variability of each gene or covariate is higher within clusters having a large number of subjects, e.g., 75, presumably because different endotypes have been combined in the cluster.
It does not suffice to refer to the questionable comparability between different countries and measures in order to interpret the observed variability of results.
I ranges from 0 to 100% and can be interpreted as the variability of study-specific effect estimates attributable to true between study effects.
Therefore, our aim was to introduce a method to calculate a confidence ellipse around the two components of the NRI which reflects the precision of the estimates and can help interpret the magnitude and variability of the observed effects.
Multivariate analysis manifested HDL, HbA1c, sex, history of hypertension and COPD as the most powerful and independent parameters of sST2, that predict and/or interpret the 81% of sST2 variability in this group.
From this plot, we can clearly see that an inappropriate exchangeable assumption leads to a substantial blur between the estimated variability of the interaction parameters of modified and unmodified areas, and that interpreting any patterns of the variability of the interactions as corresponding to "true variability" would be difficult.
