Table 4 Summary of hierarchical... | Emerald Publishing

Table 4

Summary of hierarchical regression analysis for variables predicting CA (N = 241)

Variables	B	SE B	β
Step 1
Gender of follower	1.4	0.73	0.13
Race of follower	−1.5	0.77	−0.12
Age of follower	−1.5	0.41	−0.03
Education of follower	−0.50	0.62	−0.10
Tenure with supervisor ΔR² = 0.06	−0.70	0.40	−0.14
Step 2
Gender of follower	1.3	0.76	0.11
Race of follower	−2.4	1.0	−0.20*
Age of follower	0.30	0.50	0.05
Education of follower	−0.43	0.61	−0.05
Tenure with supervisor	−0.75	0.40	−0.15*
Gender dissimilarity	−0.10	0.78	−0.01
Race dissimilarity	1.5	1.0	0.13
Age dissimilarity R² = 0.08, ΔR² = 0.02	0.58	0.40	0.12

Variables	B	SE B	β
Step 1
Gender of follower	1.4	0.73	0.13
Race of follower	−1.5	0.77	−0.12
Age of follower	−1.5	0.41	−0.03
Education of follower	−0.50	0.62	−0.10
Tenure with supervisorΔR² = 0.06	−0.70	0.40	−0.14
Step 2
Gender of follower	1.3	0.76	0.11
Race of follower	−2.4	1.0	−0.20*
Age of follower	0.30	0.50	0.05
Education of follower	−0.43	0.61	−0.05
Tenure with supervisor	−0.75	0.40	−0.15*
Gender dissimilarity	−0.10	0.78	−0.01
Race dissimilarity	1.5	1.0	0.13
Age dissimilarityR² = 0.08, ΔR² = 0.02	0.58	0.40	0.12

Note(s): CA is the dependent variable. CA is measured using the PRCA-24. *p < 0.05; **p < 0.01