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We examined variance inflation factors for multicollinearity and case diagnostics for evidence of influential observations.
We further examined variance in UAs by stratifying models on known characteristics that have been suggested to influence UAs.
As a final assessment, we examined variance on the 10 ACT concepts among the 25 nursing homes and also between care units within each nursing home.
For these analyses, we examined variance in each of the distinct emotion states we studied, as well as in mean positive affect and negative affect.
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Multicolinearity between covariates was assessed in models by examining variance inflation factors (VIF); all VIFs were less than 30.
We checked for multicollinearity by examining variance inflation factors.
Multi-collinearity was ruled out by examining variance inflation factors.
Models were also assessed for collinearity by examining variance inflation factors and conditional indices.
We further considered multi-collinearity by examining variance inflation factors (VIFs).
We verified the absence of collinearities by examining variance inflation factors.
We next focused our efforts on examining variance associated with probes of alternative sequence directed against the same target gene.
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