Skip to main content

Table 1 Characteristics of those heavily victimised over ICVS sweeps

From: The global crime drop and changes in the distribution of victimisation

Variable Top crime decile vs remainder 1989 Top crime decile vs remainder 2000 Top crime decile vs remainder 1989 (vehicle) Top crime decile vs remainder 2000 (vehicle) Top crime decile vs remainder 1989 (property) Top crime decile vs remainder 2000 (property) Top crime decile vs remainder 1989 (personal) Top crime decile vs remainder 2000 (personal)
Number of cars (fewer) <.001 <.001 <.001 <.001 <.005 Ns <.005 Ns
Number of bikes (fewer) <.001 <.001 <.001 <.001 Ns Ns <.005 <.001
Gender (male vs female) <.001 Ns Ns Ns Ns <.05 <.001 <.005
Age (younger) <.001 <.001 <.001 <.001 <.005 <.05 <.001 <.001
Household size (fewer) <.001 <.001 <.001 <.001 Ns Ns Ns Ns
Adult number (fewer) Ns Ns <.005 <.05 Ns Ns Ns <.001
Town size (less than 50,000 vs rest) <.001 <.001 <.001 <.001 <.05 Ns <.05 <.005
Accommodation type (detached + semi-Detached vs other) <.001 <.005 <.001 <.001 <.05 Ns Ns Ns
Accommodation (owner-occupied vs rental) <.001 Ns Ns Ns <.005 Ns <.05 Ns
Employment (yes vs no) <.005 <.001 <.05 <.001 Ns Ns Ns Ns
Income (less) <.001 Ns <.001 <.001 Ns Ns Ns <.05
  1. It summarises the analyses. Contingency table analysis was used for categorical variables and the Mann–Whitney U Test for ordinal variables. For every variable, the direction of the difference is the same in the years compared. The italicised and underlined word or phrase in the left column of the table is the over-represented alternative. For example, households in rental accommodation were more victimised than owner-occupied homes. Cell entries are probabilities of the relationship
  2. Categorical variable statistics are Chi square with 1° of freedom. The ordinal variable statistic is z