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. 2017 Oct 17;6(4):611–619. doi: 10.1556/2006.6.2017.064

Table 3.

Hierarchical binary logistic regression models for excessive online gaming

Model 1 Model 2 Model 3
B OR 95% CI for OR B OR 95% CI for OR B OR 95% CI for OR
Constant −2.281 0.102 −2.537 0.079 −2.559 0.077
Gender (girl = ref. +) 2.575 13.137 (9.628, 17.924)** 2.559 12.924 (9.466, 17.645)** 2.560 12.931 (9.471, 17.655)**
School (grammar school = ref. +)
Secondary with graduation 0.279 1.322 (1.032, 1.695) 0.317 1.372 (1.069, 1.763) 0.318 1.374 (1.069, 1.767)
Vocational 0.016 1.016 (0.786, 1.315) 0.096 1.101 (0.844, 1.435) 0.097 1.102 (0.844, 1.440)
Age (in years) −0.108 0.898 (0.800, 1.007) −0.091 0.913 (0.812, 1.025) −0.090 0.914 (0.813, 1.028)
Daily smoking (no = ref. +) −0.380 0.684 (0.514, 0.910)** −0.380 0.684 (0.513, 0.911)**
Binge drinking (no = ref. +) 0.054 1.055 (0.860, 1.296) 0.053 1.055 (0.859, 1.295)
Marijuana use (no = ref. +) −0.029 0.972 (0.778, 1.214) −0.029 0.972 (0.777, 1.215)
Family composition (complete family = ref. +)
Reconstructed 0.031 1.032 (0.773, 1.377)
Other −0.031 0.969 (0.774, 1.214)
Hosmer and Lemeshow testa 9.263 3.547 2.472
Sig. 0.321 0.896 0.963
Nagelkerke R2 0.185 0.188 0.188

Note. Dependent variable: excessive online gaming (coded as 1), non-excessive online gaming (coded as 0). OR: odds ratio.

a

Hosmer–Lemeshow statistics indicates a poor fit if the significance value is less than 0.05.

**

p < .01.