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> -wrap-foot> A similar linear model explained much less variation of recombination in the chimpanzee genome (table 3).
Our model explained much of the variation in chronological age, in line with previous research showing that multivariate brain imaging analysis can accurately predict chronological age.
If a model was fitted with only GC content, the effect was positive although the model explained much lower variability than a model with only recombination rate (results not presented).
Contrary to this claim in our regression analyses with hospital setting as a predictor variable, the high R2 value indicates that our model explained much of the variation in patient satisfaction.
For all morphometric traits, the full model explained much more variation in the data (range: 11.7-56.5%, mean = 32.1%, SD = 15.4, Table 1) than did the associated random model, (t-test comparing mean percent variation explained by full models and random models: t = 5.08, df = 7.59, p = 0.001).
An explained ward level variance of 64%, 64% and 53% in the models with quality assessed by relatives, staff and field observations respectively, shows that the predictors in the model explained much of the variation in quality of care between the wards and that common method variance was a minor problem in the study.
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Indeed, we expect that the model explains much of the oral flora in most vertebrate species, even most of the oral flora in dragons.
The GWR model explains much of the variability in the data (r2 = 0.72) and as its residuals have no spatial structure, the model does not appear to have systemic deficiencies.
Our observations that despite hyperphagia, circulating insulin levels remain in a fasted state in Px rats are also in support of the hypothesis that insulin deficiency in this model explains much of the attenuation in body mass gain and muscle mass growth.
Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission.
However, these models explain much more of the variance than those models which did not include mental health and emotional role scores.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com