3417.0.55.001 - Microdata: Australian Census and Migrants Integrated Dataset, 2011 Quality Declaration 
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 14/02/2014  First Issue
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Image: Using the MCDE Dataset in TableBuilder USING THE DATASET IN TABLEBUILDER



The TableBuilder User Manual is a comprehensive reference guide for the web interface - TableBuilder. It includes information on 'Getting Started', 'Customised Data' and 'Interpreting Results' from ABS data.

Information relating to the linking methodology, scope, coverage, data collection, measures of error and interpretation of results are explained in the Linking Methodology section.


Continuous data items

The Australian Census and Migrants Integrated Dataset (ACMID), 2011 contains several continuous data items. The calculation of sums, medians and means are only possible for continuous data items AGEP (Age), TISP (Number of children ever born) and HRSP (Hours worked).

For information regarding the calculation of 'Sums', 'Median', 'Mean' and Ranges see the sections Create Custom Ranges and Add Sum, Median or Mean to a Table.

Multi response data items

Data items produced from a survey or Census that allow a respondent to fall into multiple categories are referred to as multiple response data items. For example, the ACMID, 2011 contains the Ancestry variable that allows respondents to report up to two ancestries on their Census form. Respondents do not have the option of ranking their answers to the ancestry question, so where a respondent reports two ancestries, those two ancestries have equal standing. The basis for allocating ancestries to the variables ANC1P and ANC2P is administrative only and is based on the order in which they are processed.

Example of differences in counts of responses for ANCP 1 and ANCP 2 are shown below.

Image: Example of counts of responses for ANCP 1 Image: Example of counts of responses for ANCP 2

In accordance with the Census and Statistics Act 1905, all the data in TableBuilder are subjected to a confidentiality process before release. This confidentiality process is undertaken to avoid releasing information that may allow the identification of particular individuals, families, households, dwellings or businesses.

Processes used in TableBuilder to confidentialise records include the following:
    • perturbation of data
    • table suppression
    • field exclusion rules.

Perturbation of data

To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves small random adjustments of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics.

The introduction of these random adjustments result in tables not adding up. While some datasets apply a technique call additivity to give internally consistent results additivity has not been implemented on the ACMID, 2011. As a result, randomly adjusted individual cells will be consistent across tables, but the totals in any table will not be the sum of the individual cell values. The size of the difference between summed cells and the relevant total will generally be very small, as demonstrated below.

Image: Example of perturbed data for males and females

(Sum of cells = 631,840.4 + 679,813.7 = 1,311,654.1. Difference of 3.8 relative to displayed total)

Table suppression

Some tables generated within TableBuilder may contain a substantial proportion of very low counts within cells (excluding cells that have counts of zero). When this occurs, all values within the table are suppressed in order to preserve confidentiality. The following error message displayed at the bottom of the table indicates when table suppression has occurred.

Image: Example of table suppression error message

Field exclusion rules

To ensure confidentiality, TableBuilder prevents the cross-tabulation of certain variables which could result in respondents being identified. These are known as field exclusion rules. Field exclusion rules exist when two or more data items cannot be added to the same table due to confidentiality risks within the data.