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2901.0 - Census Dictionary, 2006 (Reissue)  
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 23/08/2007  Reissue
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Contents >> Short Definitions and Classifications - 2006 >> Imputation Flag for Place of Usual Residence (IFPURP) - Characteristics 2006

Imputation Flag for Place of Usual Residence

On this page:
Description
Classification
Quality Statement


Description

This variable provides information on the level of response a person provided to the 'place of usual residence' question. Some people may provide an incomplete address of usual residence, and this flag indicates the geographic level at which imputation was then required. This variable can also be used to flag instances where people did not report their Usual Address Indicator Census Night (UAICP) and when it was possible to derive this indicator. For example, if a person was enumerated in Victoria and they provided a Tasmanian place of usual residence then UAICP is derived to 'Elsewhere in Australia'.


Classification

Applicable to: All persons

1 Not imputed - State/territory, SLA and CD stated
2 CD imputed - State/territory and SLA stated
3 SLA and CD imputed - Capital City provided
4 SLA and CD imputed - State/territory only provided
5 State/territory, SLA and CD imputed

Total number of categories:
one digit level 5
two digit level 15

More Detailed Description


Quality Statement - Imputation Flag for Place of Usual Residence (IFPURP)

There are many aspects which can affect the quality of Census data; the following information should be considered when viewing data on Imputation Flag for Place of Usual Residence (IFPURP).

For 2006, every person counted in the 2006 Census has been given a place of usual residence (PURP) down to the Collection District (CD)Level and the number of persons who had any level of PURP imputed (State, Statistical Local Area, or Collection District) was 1,157,614 (5.8%). In 2001, the lowest level of imputation was applied at the SLA level (and therefore the measurement of imputation in 2001 is not comparable with 2006). Most of the imputation in 2006 is attributable to the 4.1% of persons (including those imputed as overseas visitors) in dwellings which were occupied on Census Night but did not return a completed form. Person counts for these dwellings are imputed as well as some basic demographic data such as PURP.

The ABS aims to produce high quality data from the Census. To achieve this, extensive effort is put into Census form design, collection procedures, and processing procedures.

There are four principal sources of error in Census data: respondent error, processing error, partial response and undercount. Quality management of the Census program aims to reduce error as much as possible, and to provide a measure of the remaining error to data users, to allow them to use the data in an informed way.

When completing their Census form, some people do not answer all the questions which apply to them. In these instances, a 'not stated' code is allocated during processing, with the exception of non-response to age, sex, marital status and place of usual residence. These variables are needed for population estimates, so they are imputed using other information on the Census form, as well as information from the previous Census.

The processing of information from Census forms is now mostly automated, using scanning, Intelligent Character Recognition and other automatic processes. Quality assurance procedures are used during Census processing to ensure processing errors are kept at an acceptable level. Sample checking is undertaken during coding operations, and corrections are made where necessary.

The Census form may be completed by one household member on behalf of others. Incorrect answers can be introduced to the Census form if the respondent does not understand the question or does not know the correct information about other household members. Many of these errors remain in the final data.

More detailed information on data quality is available in the 2006 Census Dictionary (cat. no. 2901.0), in the section titled Managing Census Quality.





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