4530.0.55.002 - Microdata: Crime Victimisation, 2012-13 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 28/04/2014   
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For general information relating to TableBuilder or instructions on how to use features of the TableBuilder product, please refer to the User Manual: TableBuilder, June 2013 (cat. no. 1406.0.55.005).

Outlined below is more specific information relevant to the Crime Victimisation TableBuilder. This information should help users better understand and interpret the data.


Weighting is the process of adjusting results from a sample survey to infer results for the total population. To do this, a 'weight' is allocated to each record. The weight is the value that indicates how many population units are represented by each sample unit.

Both person and household estimates can be obtained from the Crime Victimisation TableBuilder. Each type of estimate uses a different weight (or 'Summation Option') and it is essential that the correct one is selected when specifying tables. Weights are selected from the Summation Options, as shown below:

Summation Options

Generally, as the Socio-demographic and Personal Crime Level relates to people a person weight is attached in the Summation Options. Similarly, as the Household Crime Level relates to households a household weight is attached.

However, the default weight when producing any table using the Crime Victimisation TableBuilder is the person weight (in bold in the image above) which is automatically applied to any table being generated. If generating a table from the Household Crime Level, the weight will usually need to be changed. A weight shown in bold, such as in the image above, indicates the weight being used in the table. Placing a tick in a 'Sum' tick box and then adding it to a row or column in the table will select a different weight.

While the default is person weight, it is also possible to specifically select person weight through Summation Options. To estimate the number of persons with certain characteristics (e.g. 'Number of assaults experienced by a person in the last 12 months') the weight listed under the category heading Socio-demographic and Personal Crime Level must be used. To specifically select a person weight through Summation Options:
1. Click on the blue triangle 'twistie' () next to the Summation Options line
2. Ensure all 'Sum' tick boxes are blank
3. Click on the Socio-demographic and Personal Crime Level 'twistie'
4. Click on the Person Weight 'twistie'
5. Click on the Sum tick box
6. Add the person weights to your table by clicking on add to row or add to column

To estimate the number of households with certain characteristics (e.g. 'Number of break-ins experienced by households in the last 12 months') the household weight listed under the category heading Household Crime Level must be used. The same process as above can be followed, ticking the 'Sum' tick box under the Household Crime Level 'twistie' instead.

The following table summarises the weights recommended for use with each of the levels:

LevelSummation option weightsUnit of measure
Socio-demographic and Personal Crime LevelNumber of Socio-demographic and Personal crime data itemsPerson
Household Crime LevelHousehold Crime Level Data ItemsHousehold
Household Crime Level x Socio-demographic and Personal Crime Level (except Demographics, Education, Labour Force, Personal Income)Household Crime Level Data ItemsHousehold


Some continuous data items are allocated special codes for certain responses (e.g. 9999 = 'Not applicable'). When creating ranges for such continuous items, special codes are NOT included. Totals, therefore, represent only 'valid responses' for continuous data items rather than all responses (including special codes).

For example:

The following table shows the responses for 'Weekly personal income from all sources' by 'Sex of person'. The continuous values of the data item are contained in the 'A valid response was recorded' row. If the actual continuous values are to be displayed then it is necessary to create a range for them.

Table demonstrating continuous data item
Here is the same table with a range applied for the continuous values of 'Weekly personal income from all sources' (IncExample). Note that the numbers of respondents for the other responses 'Not applicable', 'Valid reading not obtained' and 'Not measured' no longer contribute to the table.

Table demonstrating continuous data item in ranges

Any special codes for continuous data items are listed in the Data Item List.


Apart from the Field Exclusion Rules that are applied in TableBuilder, there are minimal restrictions on the items that can be selected to appear in a table. That is, generally, users are able to cross-tabulate any variable with any other variable on the file. However, often the resulting table is not logical. For example, 'Whether household experienced a break-in in the last 12 months' by 'Whether weapon used in most recent incident of physical assault' cross-tabulates two different types of crimes which have no meaningful connection.

The following table summarises when variables should and should not be cross-tabulated.

Socio-demographic and Personal Crime
Data Items
Household Crime Level Data Items
Socio-demographic and Personal Crime Data Items
        Exception: Index of relative socio-economic index disadvantage - Deciles
      Household Demographics
      Labour Force
      Income (see rows below)
        Household Income
        Personal Income
      Crime Person Level
Household Crime Level Data Items
See column 3


To ensure confidentiality, TableBuilder prevents the cross-tabulation of certain variables which could result in respondents being identified. These are know as field exclusion rules. In the Crime Victimisation TableBuilder these restrictions have been applied to the sub-state geographic and SEIFA data items such that only one sub-state geographic or SEIFA data item can be included in any one table.

The sub-state geographic and SEIFA data items available are:
  • Greater Capital City Statistical Areas
  • Remoteness Areas - ASGS
  • Section of State - ASGS
  • SEIFA - Index of Relative Socio-economic Advantage and Disadvantage - 2011 - SA1 - Deciles National
  • SEIFA - Index of Relative Socio-economic Disadvantage - 2011 - SA1 - Deciles National

If field exclusion rules exist for certain variables, users will see the following message: “Maximum number of fields in exclusion group exceeded.”


Crime victim surveys are best suited to measuring crimes against individuals or households with specific victims. Victims need to be aware of and recall what happened to them and how it happened, as well as be willing to relate what they know to interviewers.

Not all types of crime are suitable for measurement by household surveys. No reliable information can be obtained about crimes without specific victims, such as trafficking in narcotics. Crimes of which the victim may not be aware cannot be measured effectively - some crimes involving deception and attempted crimes of many types may fall into this category. It may also be difficult to obtain information about some crimes such as sexual offences and assault committed by other household members due to the sensitivity of the crime and an increased reluctance to disclose. Some of these crimes may not be fully reflected in the data collected. Household survey data excludes crimes against commercial establishments or government agencies.

This survey covered only selected types of personal and household crimes. Personal crimes covered in the survey were physical assault, threatened assault, robbery and sexual assault. Household crimes covered were break-in, attempted break-in, motor vehicle theft, theft from a motor vehicle, malicious property damage and other theft.

For this survey the definition of total victims is restricted to those crimes included in the survey and does not represent all crime in Australia. Information collected in this survey is essentially 'as reported' by respondents and hence may differ from that which might be obtained from other sources or via other methodologies. This factor should be considered when interpreting the estimates and when making comparisons with other data sources.


Tables generated from sample surveys will sometimes contain cells with zero values because no respondents that satisfy the parameters of the cell were in the survey. This is despite there being people in the population with those characteristics. That is, the cell may have had a value above zero if all persons in scope of the survey had been enumerated. This is an example of sampling variability which occurs with all sample surveys. Relative Standard Errors cannot be generated for zero cells. Whilst the tables may include cells with zero values, the ABS does not publish such zero estimates in Crime Victimisation, Australia, 2012-13 (cat no. 4530.0) and recommends that TableBuilder clients do not use these data either.


Data was collected using Computer Assisted Interviewing (CAI), whereby responses were recorded directly onto an electronic questionnaire in a notebook computer, usually during a telephone interview. A copy of the household survey questions used to collect the Crime Victimisation is available (see the Crime Questionnaire in the Downloads tab). Response categories in the data collection instrument represent input categories and are not always available as separate output categories on the TableBuilder file as categories are collapsed for output to improve data quality and maintain confidentiality. However, it is important that users consider precise question wording, question order and sequencing and the range of input categories to assist them to interpret the data.


A number of the survey's data items allow respondents to provide more than one response. These are referred to as 'multi–response data items'. An example of such a data item is shown below. For this data item, respondents can report all types of contact which they have had with the police in the last 12 months.

Multiple-response data item

When a multiple response data item is tabulated, a person is counted against each response they have provided. As a result, each person in the appropriate population is counted at least once, and some persons are counted multiple times. Therefore, the total for a multiple response data item will be greater than or equal to the sum of its components. Multi–response data items can be identified by the initials 'MR' in the data item list, which can be accessed from the Downloads page. In the example below, the sum of the components is 18,411,700 whereas the total population is 18,398,900.

Multiple-response data item

Most data items include a 'not applicable' category. The 'not applicable' category comprises those respondents who were not asked a particular question(s) and hence are not applicable to the population to which the data item refers. The classification value of the 'not applicable' category, where relevant, is shown in the data item list (see the Data Item List in the Downloads tab).

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