Table 2.
Predictors | Equation 1 | Equation 2 | Equation 3 | ||||||
---|---|---|---|---|---|---|---|---|---|
(criterion: cyberloafing) |
(criterion: self-control) |
(criterion: cyberloafing) |
|||||||
B | 95%CI | β | B | 95%CI | β | B | 95%CI | β | |
Gender | 2.69 | (-0.98, 6.37) | 0.10 | -0.42 | (-1.97, 1.14) | -0.04 | 2.48 | (-1.12, 6.08) | 0.096 |
Age | -0.22 | (-0.54, 0.10) | -0.098 | 0.18 | (0.049, 0.32) | 0.19∗∗ | -0.13 | (-0.45, 0.19) | -0.056 |
CFC | -0.49 | (-0.77, -0.21) | -0.25∗∗ | 0.25 | (0.13, 0.37) | 0.29∗∗∗ | -0.36 | (-0.65, -0.07) | -0.18∗ |
Self-control | -0.52 | (-0.86, -0.17) | -0.22∗∗ | ||||||
R2 | 0.08∗∗ | 0.13∗∗∗ | 0.13∗∗∗ |
Each column set is a regression equation that predicts the criterion at the top of the column. Gender was dummy coded such that 0 = “female” and 1 = “male”. ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001.