Sentence examples for the proportion of variability from inspiring English sources

The column in between (R) represents the proportion of variability explained in a particular outcome variable by its set of predictor variables.

The proportion of variability in annual rates explained by prevention variables raised from 92%, with respect to the empty model, to 97% when calculated with respect to the model adjusted by age and sex, thus meaning a 5% variability in hospitalisation rates due to changes in age-sex population structure from 1996 to 2006.

What these studies allow us to do is estimate the heritability of an outcome - the proportion of variability in the outcome that can be attributed to genetic factors across a population (and therefore also the proportion attributable to environmental factors).

This had a negligible effect on the proportion of variability and was therefore left out of the final GAM analysis.

We also found that there was a lower rate of fractures in rural and less densely populated municipalities, and that place of residency affected the proportion of variability.

The latter reveals the proportion of variability in a meta-analysis that is the result of between-study variation and not error within studies due to random sampling.

The proportions of variability (effect size) in the ranked dependent variables accounted for by grouping variables were >0.20 (medium per Cohen), indicating a fairly strong relationship between sepsis and the expression levels of hGR protein, cortisol, extracellular HSP72 and 90α, SAPS-III, IL-6, procalcitonin (PCT), age, sex, and mortality (Table 1).

Among them, the proportions of variability in non-coding regions ranged from 0 to 44.4% with a mean value of 1.79%, which were twice as much as in the coding regions (0.72% on average).

We sought to quantify the proportion of total variability due to movement variability in digitizing marker and no-marker conditions in treadmill running.

It is interpreted as the proportion of the variability of the dependent variable explained by the model.

The R2 value gives the proportion of the variability in total scores explained by different exposure variables.