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. 2018 Aug 1;4(3):343–364. doi: 10.1007/s40865-018-0087-8

Table 1.

Results of fixed effects models for cyber-offending and traditional offending

Characteristic Cyber-offending Traditional offending Model comparison
OR SE OR SE χ2 (df)
Household composition 11.66 (4)*
 Alone
 With partner 0.69* 0.11 0.79*** 0.00 0.75 (1)
 With partner and child 0.54*** 0.09 0.81*** 0.00 5.79 (1)*
 With child 1.81* 0.53 1.07*** 0.01 2.83 (1)
 Other 0.84 0.12 0.98*** 0.00 1.04 (1)
Employment 1.40 (2)
 Not employed
 Employed non-IT 0.90 0.10 0.93*** 0.00 0.06 (1)
 Employed IT 1.14 0.28 0.89*** 0.01 1.02 (1)
Education 0.74 (2)
 Not in education
 In non-IT education 1.10 0.24 0.92*** 0.01 0.63 (1)
 In IT-education 1.06 0.41 0.88*** 0.03 0.23 (1)
Exposure days 1.12 0.40 1.39*** 0.01 0.38 (1)
Days institutionalizedb 0.52 0.23 0.69*** 0.01 0.34 (1)
All characteristics combined (χ2(df)) 227.74 (21)***
N (person-years) 8752 11,840,665
Unique individualsa 870 1,144,740

p < .10; *p < .05; **p < .01; ***p < .001 (two-tailed)

aAbsolute numbers of unique suspects are rounded to multiples of ten

bIncludes (but is not restricted to) incarceration

Separate year dummy variables were included in the models to control for age and period effects, but these are not displayed in the table

OR odds ratio

SE standard error

df degrees of freedom