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The jackknife estimator represents the information provided by a given variable that is not present in the other variables.
An alternative measure of the relative importance of different explanatory variables is the increase (or decrease) in the multiple R-square (the proportion of the total sums of squares explained by a given variable) of a model when an explanatory variable is added (or removed).
All variables directly or indirectly caused by a given variable are called its descendants.
– Cox-model coefficient of modification of recurrence hazard by a given variable (i.e. gene expression); P – P value computed using Cox's proportional hazard analysis.
Ideas for future development of AMGET include the insertion of the area under the curve in the post hoc fits plots or the stratification of the VPC plots by a given variable.
Because the MU can be applied to the same data but testing different explanatory factors, it can quantify how each explanatory factor partitions the same morphospace defined by a given variable (here RWs) or set of variables outlining more general morphospace.
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Type 2 will be addressed by mapping estimates of a given variable from one country where data are available to another, based on the age group and gender.
Numerical analyses of remotely sensed data may valuably contribute to an understanding of the vegetation/land surface interface by pointing out at which scales a given variable displays a high level of spatial variability.
Tests of this sort thus implicate not just the familiar judicial challenge of evaluating a given variable by reference to an established doctrinal criterion, but also the less familiar (and often unnoticed) challenge of extracting from a fact pattern an operative characterization of the variable to be evaluated.
The proportional hazards assumption was verified by comparing the Kaplan-Meier curve to the Cox predicted curve for a given variable and by assessing the parallel nature of curves in log-log plots.
The communality measures the percent of variance in a given variable explained by all the factors jointly and may be interpreted as the reliability of the indicator.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com