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High Quality Data
As with other statistical collections, the ABS strives to ensure that high quality data are obtained from the Census. To this end, extensive effort is put into the form design, collection procedures, public awareness campaign, accurate processing of the information collected and the release of data.
The method employed to obtain information in the Australian Census is one of self-enumeration in which each household is asked to complete the Census form with relatively little assistance from the Census Collector. To make sure that this approach is successful and ensure collection of the right data, a series of tests is conducted before each Census to gauge public reaction to the form and the questions being asked.
As well as making sure that the right questions are asked, it is essential for the achievement of quality Census data that everybody understands the importance of being counted and of giving the right answers in the Census. A crucial factor in this respect is the public awareness campaign referred to in the Collection section.
For all parts of the field operation, national quality assurance procedures are implemented to ensure the best possible data quality and the maximum coverage of households.
For the 2011 Census these quality assurance procedures will be improved by the use of an online Census Field Portal (CFP), and through the use of the internal Reconciliation System. The CFP links the Census Management Unit (CMU) field supervisors through a web-based application. Information from the CFP and the Reconciliation System gives the CMUs the ability to track field activity rapidly, enabling early identification of areas where delivery or collection is not proceeding smoothly.
Where this is occurring, extra assistance and support can be provided promptly, with additional intensive follow-up being conducted in relevant areas where necessary.
Data Processing Centre
Once the forms are in the Census DPC, quality assurance procedures are implemented at all phases of processing to maximise the accurate recording of information collected and to eliminate as far as possible any inconsistencies in coding responses. For example, after automatic and online coding, a sample of forms is manually recoded and inconsistent answers compared by an adjudicator to determine the source of the error. This information, along with reports from coders, is examined by continuous improvement teams, who have the responsibility for identifying quality problems and recommending ways in which quality can be improved. Coding procedures, indexes, processing systems and training of staff are the key areas where changes can lead to improved data quality during processing.
Despite these efforts, the Census, like all statistical collections, is subject to a number of sources of error, and some of the errors may be difficult to detect and correct. Testing has indicated the effect of these errors is generally slight, although it could be more significant for analysis of data for small groups or very detailed cross-classifications.
Evaluating the Outcome
As part of the field operation, an extensive evaluation is conducted. This evaluation includes all levels of field staff and Census Management Units and is conducted to ascertain the usefulness of manuals and training, as well as the Census field systems developed to support the field process. The outcomes from this evaluation are used to inform decisions on all parts of the field operation in the next Census.
After the Census, an evaluation of the Census data is carried out to inform users of the data about its quality, and to help plan the next Census. Investigation of the effect of partial response, consistency checks between related questions, comparisons with data from other sources and demographic analysis are undertaken for various Census topics.
Much of the information gathered about the quality of Census data will be distributed in the form of data quality statements that may accompany or be referenced by Census data on the ABS website. There may be more specialised data quality evaluation reports on issues or topics of interest after Census data has been released. This information helps the ABS to plan for the next Census.
Sources of Error
Despite efforts to obtain full coverage of people and dwellings, it is inevitable that a small number of people will be missed and some will be counted more than once. In Australia more people are missed from the Census than are counted more than once. The net effect when both factors are taken into account is referred to as the net undercount.
As well as affecting the total population counts, undercounting can bias other Census statistics because the characteristics of missed people are different from those of counted people. In Australia, rates of undercounting vary significantly for different population groups depending on factors such as age, sex and geographic area. A measure of the extent of undercounting is obtained from a sample survey of households undertaken shortly after the Census, called the Post Enumeration Survey. The estimate of the number of people who should have been counted in the 2006 Census was 20,402,459 people. The actual 2006 Census count for Australia was 19,852,973 people. The difference (549,486 people) is the net undercount (2.7%) for Australia.
More information on the net undercount for the 2006 Census can be found in 2940.0: Census of Population and Housing - Details of Undercount, Aug 2006.
People who are counted in the Census do not necessarily answer all the questions which apply to them. While questions of a sensitive nature are generally excluded from the Census, all questions have an element of non-response. However, this element is generally low. In those instances where a householder does not provide a response to a question, a 'not stated' code is allocated during processing, with the exception of non-response to age, sex, marital status and the SA1 of usual residence. This data is used in population estimates and so these variables are imputed, using other information on the Census form and specially constructed random tables based on the distribution of the population according to these variables.
Computer editing procedures are used to detect and correct obvious errors made by individuals in completing the form (for example, a six year old person in the labour force). However, such procedures cannot detect and correct all householders' errors and some remain in final output.
Errors created during the processing of the Census are kept at an acceptable level by means of quality assurance procedures. These involve sample checking during coding operations, and taking corrective action where necessary.
Introduced Random Adjustment
Minor adjustments are made to Census data prior to release to allow the maximum of detailed Census data possible to be released without breaching the confidentiality of individual responses. For this reason, great care should be taken when interpreting data in small cells, since randomisation, as well as possible respondent and processing errors, have a greater proportional impact on them than on larger cells.
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