Sentence examples for maximum variance Inflation from inspiring English sources

With respect to multicollinearity, we report the maximum variance inflation factors (VIFs) for each variable in Table 4.

The reciprocal of tolerance (also known as the maximum Variance Inflation Factor - VIF) (Belsley et al. 1980; Belsley 1984; O'brien 2007) can be expressed as: VIC=left(frac{1}{left 1-{R}_i^2right)}right) (7 where tolerance of the ith variable is 1 less, the proportion of variance which is ( {R}_i^2 ) (O'brien 2007).

The maximum Variance Inflation Factor (VIF) did not exceed 3.9 so that multicollinearity may be neglected.

No multicollinearity was found among the independent variables (the minimum tolerance was 1.06 and the maximum variance inflation factor (VIF) for multicollinearity was 2.96).

We also limited the degree of multicolinearity among the chosen variables by ensuring that the maximum variance inflation factors of the sets of four variables were less than 4.0 and the pairwise correlations of rp were less than 0.7.

Multicollinearity was present only at a moderate level throughout the analyses; in the fully adjusted model, maximum variance inflation factor was <1.42 for women and <1.30 for men, suggesting that jointly explained variance would not greatly interfere with the interpretation of partial beta weights.

Besides, the maximum of the observed generalized variance inflation factors was 2.08 for age which indicates the absence of serious multicollinearity problems.

Correlations between predictor variables were low (maximum r = 0.27), and the variance inflation factors were also low (mean = 1.09; range = 1.04 1.15), indicating no issues with multicollinearity [ 33].

For both models there was no evidence of multicollinearity among the chosen variables or of influential observations: the mean variance inflation factor was 1.55 (the maximum was 2.08 for Y-coordinate) in 1995/96 and 1.39 (the maximum was 1.92 for Y-coordinate) in 2007, the Cook's distance was less than 0.3 in both cases.

Variance inflation factor (VIF) test with its maximum value of 2.68 indicates that there is no multicollinearity in the regression model.

Furthermore, multicollinearity was not an empirical problem, since the variance inflation factor (VIF) ranged from 1.02 to a maximum of 3.90, thereby being below any critical value [ 115].