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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