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Translated to multivariate analysis, significant above-chance classification, independently of its absolute value, should therefore be considered to provide similarly meaningful evidence that the region has task-relevant information but at the level of patterns of activity.
Using multivariate analysis, significant predictors of co-enrollment were identified, adjusting for confounding.
In multivariate analysis, significant impact on OS was seen for age at diagnosis, number of CLM, and chemotherapeutic treatment.
In the multivariate analysis, significant candidates were used in the models two by two and with all variables together.
To improve clinical utility, before entering into the multivariate analysis, significant continuous variables were converted into binary variables by using the overall median value as the cutoff.
By multivariate analysis, significant prognostic variables were found to be the time to first metastasis (P = 0.006), and ploidy (P = 0.011).
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*OR, odds ratio; CI, confidence interval; ref, referent; –, non-significant in multivariate analysis (although significant in univariate analysis).
The multivariate analysis showed significant results on left-sided regions.
Using multivariate analysis, no significant group effect was found.
A multivariate analysis revealed significant differences among the groups on different problem scales.
However, in the multivariate analysis no significant difference was found.
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