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Table 4 Results of the tobit regression predicting cyber-victimisation and cyber-bullying

From: Bullying in school and cyberspace: Associations with depressive symptoms in Swiss and Australian adolescents

  Cyber-victimisation Cyber-bullying Depressive symptoms (M1) Depressive symptoms (M2)
  Z Sig Z Sig Z Sig Z Sig
Gender - female 4.75 < .001 1.02 .307 3.14 .002 2.79 .005
Age 1.48 .138 .67 .502 3.58 < .001 3.31 .001
Country - Australia 4.46 < .001 4.11 < .001 -3.46 .001 -4.36 < .001
Trad. bully/victim behaviors         
   Bullies vs non-involved 2.50 .012 9.32 < .001 2.47 .014 1.86 .063
   Victims vs non-involved 8.31 < .001 4.79 < .001 9.89 < .001 8.38 < .001
   Bully-victims vs non-involved 8.96 < .001 10.6 < .001 8.89 < .001 5.60 < .001
   Bullies vs victims -3.83 < .001 3.64 < .001 -5.18 < .001 -4.53 < .001
   Bullies vs bully-victims -5.88 < .001 -3.48 .001 -6.18 < .001 -4.00 < .001
   Victims vs bully-victims -3.02 .002 -6.31 < .001 -2.33 .020 -0.68 .496
Cyber-victimisation        4.83 < .001
Cyber-bullying        1.52 .127
  1. Note: Cyber-victimisation: R2 = 14.0%; Cyber-bullying: R2 = 16.5%; Depressive symptoms (M1): R2 = 12.8%; Depressive symptoms (M2): R2 = 16.1%