This publication presents pooled data on victimisation and reporting estimates at the state and territory level. Data pooling is a statistical technique in which data from multiple survey cycles are combined to produce more reliable estimates. This effectively increases the sample size of the data set and creates more robust estimates by decreasing the associated sampling error. Pooled data can be found in Tables 25 to 29 of the publication and are recommended for use over single year state and territory estimates, due to the improved data quality and reliability, particularly for less populous states and territories and low prevalence crime types.
The pooled estimates in this release were produced by combining data from consecutive CVS reference periods (survey cycles) and dividing the weights by the number of cycles that were pooled. The estimates therefore do not correspond to one particular survey cycle but instead are an average of the estimates from multiple survey years.
State and territory data has been pooled across two consecutive years for all crime types, except for sexual assault which uses three years, due to the higher sampling error associated with this offence. State and territory data has been pooled across two consecutive years for all crime types except sexual assault, which uses three years due to the higher sampling error associated with this offence.
CVS data have been pooled based on an assessment of the survey’s comparability and consistency over cycles. In particular:
- each CVS iteration is conducted on an independent sample of the same population, and the population characteristics and variables of interest have not changed substantially from one survey to the next.
- survey questions regarding victimisation and reporting have remained consistent since the first CVS in 2008-09.
- successive CVS iterations have a similar survey design, scope and coverage, enumeration period and weighting method, indicating a high level of conceptual similarity between surveys.
The pooled reference periods are labelled according to the survey cycles they are composed of. For example, the 2008-10 pooled period combines data from the 2008-09 and 2009-10 CVS cycles, spanning from July 2008 to June 2010. While a pooled period spans multiple survey years, the pooled estimate itself represents a 12-month average, not the total number of victims over the 24-month pooled period. For example, the 2019-21 pooled victimisation estimate for physical assault averages the number of persons from the 2019-20 and 2020-21 CVS cycles who reported experiencing physical assault over the last 12 months.
To provide data users with the greatest amount of flexibility and time points, rolling time series estimates have been provided in the pooled data tables. The rolling estimates combine consecutive CVS cycles so that a survey year can be used in multiple estimates. For example, the 2009-10 CVS cycle has been combined with the 2008-09 cycle to produce 2008-10 pooled estimates, and with the 2010-11 cycle to produce 2009-11 estimates. While rolling estimates produce the greatest amount of time points, these estimates will not be independent due to the overlap in survey years, this should be taken into consideration when analysing and interpretating the data.
The estimates in the pooled data tables have not been perturbed, in contrast to estimates in the other publication tables. Instead, a different confidentiality measure has been applied and some cells have been suppressed (though included in the totals where applicable), to minimise the risk of identifying individuals. The use of a different confidentiality measure means that some pooled estimates may be higher or lower than both of the previously published single-year estimates that compose the pooled data.