4159.0.30.004 - Microdata: General Social Survey, Australia, 2014 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 17/09/2015  First Issue
   Page tools: Print Print Page Print all pages in this productPrint All

This document was added or updated on 23/09/2015.


For general information relating to the TableBuilder or instructions on how to use features of the TableBuilder product, please refer to the User Manual: TableBuilder (cat. no. 1406.0.55.005).

The TableBuilder dataset contains all the data applicable to the General Social Survey (GSS) topic. Information on the structure is provided in the File Structure section.


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 General Social Survey 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;

Generally, as the Person level relates to people, a person weight is attached in the Summation Options. Similarly, as the Household level relates to households, a household weight is attached.

However, the default weight when producing any table using the GSS TableBuilder is the household weight, which is automatically applied to any table being generated. If generating a table from the Person 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.

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

LevelSummation option weightsUnit of measure
Household levelHousehold weight (1A)Households
Person levelPerson weight (5A)Persons
Voluntary work levelVoluntary work weight (6C)Instances of volunteering
Access to services levelAccessing services weight (8E)Services had difficulty accessing


TableBuilder includes a number of continuous variables which can have a response value at any point along a continuum. Some continuous data items are allocated special codes for certain responses (e.g. 998 = 'Not applicable'). When creating ranges in TableBuilder for such continuous items, special codes will automatically be excluded. Therefore the total will show only 'valid responses' rather than all responses (including special codes).

For example:

The following shows the tabulation of the data item 'Age of youngest child in household'. The continuous values of the data item are contained in the 'A valid response was recorded' row. To show the actual continuous values in a table, a range must be created.

Here is the same table with a range applied for the continuous values. Note that the households with a "Not applicable" response no longer contribute to the table.

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


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 adjustment 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. After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as Table Builder.


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 recommends that TableBuilder clients do not use these data.


One of the survey's data items allows respondents to provide more than one response. This is referred to as a 'multi–response data item'. For this data item respondents can report all types of cultural venues or events attended in the last 12 months.

When a multi-response data item is tabulated, a person is counted against each response they have provided (e.g. a person who "visited a public library" and "attended a movie theatre" will be counted one time in each of these two categories).

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 multi-response data item will be less than or equal to the sum of its components.

Back to top of the page