4840.0 - Microdata: Patient Experiences in Australia, 2016-17 Quality Declaration 
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 12/04/2018   
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For general information relating to TableBuilder and instructions on how to use features of the TableBuilder product, please refer to the Table Builder, User Guide (cat. no. 1406.0.55.005).

More specific information applicable to this 2016-17 Patient Experience Survey (PEx) TableBuilder product, which should enable users to understand, interpret and tabulate the data, is outlined below.


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 sample unit. The weight is the value that indicates how many population units are represented by the sample unit.

As the format of the PEx TableBuilder file is at the person level, there is only one weight provided - a person weight. That is, all tables produced provide estimates of the number of people with particular characteristics. The Summation Options section in the customised Table View panel in TableBuilder contains this weight. As there is only one weight available, the person weights will be automatically applied when producing tables.


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. 000 = '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). Continuous items with special codes have a corresponding categorical item in the Person Level Data Items that provides the ability to display data for the special code. Any special codes for continuous data items are listed in the Data Item List.


    A number of the survey's data items allow respondents to report more than one response. These are referred to as 'multiple response' data items. An example of such a data item is 'Long term health conditions'. For this data item, respondents can report more than one of the Long term health conditions they had, that lasted, or was likely to last, six months or more.

    When a multi-response data item is tabulated, a person is counted against each category for which they have provided a response. Therefore the sum of the components will be more than or equal to the total population, as some persons are counted multiple times. Multiple–response data items can be identified in the data item list, as they include 'multiple response' in the data item label. The data item list can be accessed from the Downloads tab.


    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 and can be accessed from the Downloads tab.


    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 TableBuilder. For PEx TableBuilder, perturbation was introduced in 2016-17.