Table 6.
Results of hierarchical multiple regression analysis with personal initiative at T2 as dependent variable (Study 2).
| Dependent variable: personal initiative T2 | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| EOE as moderator | LST as moderator | AES as moderator | |||||||
| B | SE | β | B | SE | β | B | SE | β | |
| Step 1: controls | |||||||||
| Age | 0.00 | 0.01 | 0.03 | 0.00 | 0.01 | 0.03 | 0.00 | 0.01 | 0.03 |
| Gender | −0.19 | 0.12 | −0.14 | −0.19 | 0.12 | −0.14 | −0.19 | 0.12 | −0.14 |
| R 2 | 0.022 | 0.022 | 0.022 | ||||||
| Step 2: main effects | |||||||||
| Job complexity T1 | 0.14 | 0.05 | 0.21* | 0.14 | 0.05 | 0.21* | 0.14 | 0.05 | 0.21* |
| EOE T1 | −0.04 | 0.08 | −0.05 | −0.04 | 0.08 | −0.05 | −0.04 | 0.08 | −0.05 |
| LST T1 | −0.14 | 0.06 | −0.22* | −0.14 | 0.06 | −0.22* | −0.14 | 0.06 | −0.22* |
| AES T1 | 0.16 | 0.07 | 0.20* | 0.16 | 0.07 | 0.20* | 0.16 | 0.07 | 0.20* |
| R 2 | 0.170 | 0.170 | 0.170 | ||||||
| Step 3: interaction | |||||||||
| Job complexity T1 * EOE T1 | −0.09 | 0.07 | −0.11 | ||||||
| Job complexity T1 * LST T1 | 0.05 | 0.06 | 0.08 | ||||||
| Job complexity T1 * AES T1 | 0.14 | 0.07 | 0.18* | ||||||
| R 2 | 0.181 | 0.175 | 0.201 | ||||||
N = 126. T1 = time 1, T2 = time 2. Gender was coded 0 = male, 1 = female. The predictors were mean-centered. B, unstandardized regression coefficient and SE, standard error. R2 = proportion of variance explained in the criterion associated by the variables.
*
p ≤ 0.05.