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Table 3 Factors associated with the diagnosis of SBD in a binary logistic regression analysis

From: Assessment of the association between non-suicidal self-injury disorder and suicidal behaviour disorder in females with conduct disorder

  Nagelkerke R2 Percentage of correctly classified subjects Variable B S.E. Wald OR 95%CI p
Model 1 0.309 81.0 STAI-X1 − 0.005 0.027 0.032 0.995 0.944–1.049 0.859
STAI-X2 −0.003 0.030 0.008 0.997 0.941–1.057 0.927
CDI 0.076 0.035 4.871 1.079 1.009–1.155 0.027
SES −0.001 0.054 0.001 0.999 0.899–1.109 0.982
GAF 0.019 0.019 2.344 0.971 0.935–1.008 0.126
NSSID 1.070 0.510 4.401 2.914 1.073–7.917 0.036
Model 2 0.273 79.6 STAI-X1 −0.006 0.026 0.058 0.994 0.944–1.046 0.809
STAI-X2 −0.006 0.029 0.037 0.994 0.939–1.054 0.848
CDI 0.089 0.034 6.775 1.093 1.022–1.169 0.009
SES −0.011 0.054 0.045 0.989 0.890–1.099 0.832
GAF −0.037 0.019 3.807 0.964 0.929–1.000 0.051
Recent-year’s number of NSSIs 0.002 0.007 0.093 1.002 0.988–1.016 0.761
Model 3 0.275 80.3 STAI-X1 −0.008 0.026 0.099 0.992 0.942–1.044 0.752
STAI-X2 −0.004 0.029 0.015 0.996 0.941–1.055 0.902
CDI 0.089 0.034 6.859 1.093 1.023–1.168 0.009
SES −0.011 0.054 0.040 0.989 0.890–1.099 0.842
GAF −0.035 0.019 3.358 0.965 0.930–1.002 0.067
Lifetime number of NSSIs 0.001 0.001 0.322 0.570 0.998–1.004 0.570
  1. Significant effects were marked with bold characters (p < 0.05)