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8111.0 - Research and Experimental Development, Higher Education Organisations, Australia, 2008 Quality Declaration 
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 26/05/2010   
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TECHNICAL NOTE DATA QUALITY


NON-SAMPLING ERROR

1 Non-sampling errors may arise as a result of errors in the reporting or processing of data. These errors can be introduced through inadequacies in the collection instrument, treatment of non-response, inaccurate reporting by data providers, errors in the application of survey procedures, incorrect recording of answers and errors in data capture and processing.

2 The extent to which non-sampling error affects the results is difficult to measure. Every effort is made to minimise non-sampling error by careful design and testing of the collection instrument, the use of efficient operating procedures and systems, and the use of appropriate methodologies.


Reliability of statistics

3 When interpreting the statistics in this release, the reliability and comparability of the estimates may be affected by the following specific non-sampling errors:

  • Many institutions provided estimates due to a lack of separately recorded data on R&D activity.
  • Data were self-classified by institutions to Field of research (FOR), Socio-economic objective (SEO) and Type of activity at the time of reporting. Some institutions may have experienced difficulty in classifying their R&D projects. The ABS makes every effort to ensure correct and consistent interpretation and reporting of these data by applying consistent processing methodologies.
  • The estimation method for R&D related overhead costs varied across institutions and reference periods. See Explanatory Notes 12 to 14.


REVISIONS

4 Revisions to previous cycle data occur on discovery of errors in the data, typically a result of the specific non-sampling errors outlined in the Reliability of statistics section above.

5 Revisions are only applied where the impact on:
  • R&D expenditure is equal to $5 million or more; or
  • Human resources devoted to R&D is equal to 25 PYE or more.

6 In processing 2008 data, revisions were applied to 2006 estimates. Revisions impacted three states and territories for expenditure and/or human resource effort devoted to R&D. Most significantly, revisions were applied to source of funds estimates for General university funds and Other commonwealth government; these were primarily a result of data being re-categorised between these sources due to misreporting in the 2006 survey.

7 Users are advised to refer to the most recently released data cubes, as revisions must be taken into consideration when interpreting results, particularly when comparing estimates over time.


COMPARABILITY OF ESTIMATES OVER TIME

8 In addition to the non-sampling errors outlined in the Reliability of statistics section, factors which may affect the comparability of 2008 estimates with those of previous cycles are described below:
  • Implementation of the Australian and New Zealand Standard Research Classification. Differences which exist between this and the previously used Australian Standard Research Classification means the change in research classification represents a break in series. Users should familiarise themselves with those differences by referring to the Australian and New Zealand Standard Research Classification (ANZSRC), 2008 (cat. no. 1297.0) if attempting to compare FOR and SEO data across reference periods.
  • Additional reporting requirements for Excellence in Research for Australia initiative have led to improved record keeping within higher education institutions. This resulted in more accurate reporting of data by a number of institutions for some R&D items in the 2008 survey. Previously these institutions could only provide estimates.


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