TABLE 2.

Multinomial Regression Model for Hacking and Detection (N = 51,059), Clustered by School (N = 1,183).

	Hacked/Not Detected		Hacked/Detected
Variables	Coef.	SE	Coef.	SE
Opportunity Characteristics
Own Computer (1 = Yes)	0.335***	0.084	0.158	0.129
Own Mobile (1 = Yes)	0.211*	0.087	–0.021	0.128
Own Room (1 = Yes)	0.082	0.053	0.100	0.086
Engagement Characteristics
Technology Use	0.144***	0.018	0.027	0.028
Piracy (1 = Yes)	1.618***	0.058	1.508***	0.090
Contextual Characteristics
Self-Control	−0.016***	0.001	−0.013***	0.002
Family Bond	−0.006***	0.001	−0.007***	0.002
Time Peers	0.045**	0.014	0.063**	0.023
Parental Supervision	−0.293***	0.034	–0.019	0.059
Demographic Characteristics
Age	0.065	0.036	0.007	0.078
Gender (1 = Male)	1.158***	0.047	0.823***	0.073
Car Ownership	0.181*	0.076	0.209	0.127
Small City	0.076	0.046	0.657***	0.067

F = 122.60***; *p < 0.05, **p < 0.01, ***p < 0.001. ¹This study was conducted in 15 western European countries (Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, The Netherlands, Portugal, Spain, Sweden, Iceland, Norway, and Switzerland), 10 eastern European countries (Cyprus, the Czech Republic, Estonia, Hungary, Lithuania, Poland, Slovenia, Armenia, Bosnia-Herzegovina, and Russia), the United States (Illinois, Massachusetts, New Hampshire and Texas), and several countries outside of Europe and North America (Aruba, Netherlands Antilles, Suriname, and Venezuela).