In addition to the general process of continuous variability analysis, we had to evolve the process of continuous individualized monitoring of individual variability metrics, where no guidelines exist.
We used the Kruskal-Wallis test to analyze the variability of the continuous variables of the study.
Nonetheless, the promise of a novel dimension of monitoring based on continuous variability analysis is supported by this observational trial, and merits the attention of future investigations.
We propose that multi-system continuous variability analysis offers the intensivist a unique monitoring tool that is capable of improving prognostication and directing therapeutic intervention.
Median and interquartile range were used to describe central tendency and variability of continuous variables, while frequencies were used to describe the distribution of categorical variables.
Frequencies were calculated for categorical questions and measures of central tendency and variability for continuous variables.
Alternatively, the vector thickness could be used to represent a continuous variable such as the variability in the original measurements, which would allow for different patterns of variability to be visualised.
The principal component analysis was used to determine causes for the variability of a set of continuous variables and rank them by importance.
Two sets of field trial data are used to investigate variability of braking: (i) continuous rim temperature data for locomotive wheels and (ii) one time measurement of wheel rim temperatures of all wheels.
