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4840.0 - Microdata: Patient Experiences in Australia, 2011-12 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 14/02/2014   
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USING THE TABLEBUILDER


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

More specific information relevant to the Patient Experience (PEx) TB, which should enable users to understand, interpret and tabulate the data, is outlined below.


COUNTING UNITS AND WEIGHTS

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

Population estimates of persons can be obtained from the 2011–12 PEx TB. When producing tables in TB, the summation option or counting unit will automatically be added to the table.

As a result of only Person level data being available on the PEx TB, there is only one set of weights on the file i.e. person. The following image shows the available Summation Options. The Person level has five options: Demographic, Income, Labour Force Items, Medical visits and Person weight. These options contain continuous data items, which are discussed below.

Graphic: Summation options - file structure


CONTINUOUS DATA ITEMS

Some continuous data items are allocated special codes for certain responses (e.g. 9999 = 'Not applicable'). When creating ranges for such continuous items for use in the TB, these special codes will NOT be included in these ranges. Therefore, the total shown only represents 'valid responses' of that continuous data item 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.

Graphic: Continuous data item - special code example

Here is the same table with a range applied for the continuous values of 'Weekly personal income from all sources' (Wkly Pers Inc Example). Note that the numbers of respondents for the other responses 'Not stated' and 'Refusal' no longer contribute to the table.

Graphic: Continuous data item - range example

Any special codes for continuous data items are listed in the Data Item List in the Downloads tab.
FIELD EXCLUSION RULES

To ensure confidentiality, TB prevents the cross-tabulation of certain data items which could result in respondents being identified. These are known as field exclusion rules. If field exclusion rules exist for certain data items, users will see the following message: “Maximum number of fields in exclusion group exceeded.”


ZERO VALUE CELLS

Tables generated from sample surveys will sometimes contain cells with zero values because no respondents that satisfied 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 and recommends that TB clients do not use these data either.


MULTI–RESPONSE DATA ITEMS
    A number of the survey's data items allow respondents to report more than one response. These are referred to as 'multi-response data items'. An example of such a data item is pictured below. For this data item, respondents can report all of the reasons they went to a hospital emergency department instead of seeing a GP on the most recent occasion.

    Graphic: Multiple-response data item - file structure example

    For the data item in the example above, a question is asked in the survey which collects all the reasons a person went to a hospital emergency department instead of a GP on the most recent occasion. As a person may indicate more than one reason, this means they can supply multiple responses to this data item.

    When a multi-response data item is tabulated, a person is counted against each category for which they have provided a response (e.g. each reason a person gives for going to an emergency department and not seeing a GP for treatment).

    Similar to a single response data item, a person not within the appropriate population will fall into the ‘Not applicable’ category (e.g. a person who did not visit an emergency department is not asked about their reasons for not seeing a GP and is therefore considered ‘Not applicable’ for this data item).

    Therefore, each person in the applicable population is counted at least once, while some persons are counted multiple times. Multi–response data items can be identified by the initials 'MR' in the data item list, which can be accessed from the Downloads tab. The total for multi-response data items is therefore less than or equal to the sum of its components. In the example below, the sum of the components is 18,571.9 whereas the total population is 18,058.9.

    Graphic: Multiple response data item - example


    NOT APPLICABLE CATEGORIES

    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. In the example above, 15,593,500 people did not visit a hospital emergency department and therefore are not applicable to the data item. 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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