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INFORMATION ABOUT 2011 to 2016 ASGS CORRESPONDENCES
So the result is that the MB in question is donating 70 per cent of its data to SA1 A, and 30 per cent of its data to SA1 B.
The benefit of using this method is that any two sets of geographic regions can have a correspondence generated for them, and that any attribute value can be distributed across the grid to be used as the weighting unit.
The ABS conducted an investigation to determine how accurately correspondences converted data. This found that while some correspondences converted data well, there were many cases where the converted data did not reflect the actual characteristics of some geographical regions. Based on these findings a quality indicator was developed to inform data users of instances where the converted data values are likely to be accurate, and where caution will be needed to be used when assessing the results.
The method that has been developed to generate the quality indicator involves a number of steps. Firstly it looks at the value that a FROM region donates to a TO region as a ratio of the whole FROM region. The next step is to examine the value that the FROM region donates to the TO region as a ratio of the whole TO region. These two values are then multiplied together to provide the component for that FROM region. This process is then repeated for each donating FROM region, with the component values then added to provide the overall score for the TO region. Based on the score returned, a textual description is then applied as to how well the ABS expects data to be converted to the TO region. This is highlighted in the example below.
Diagram 2: Illustration of 3 FROM regions to 1 TO region.
In this example there are three FROM regions A, B and C represented by the black boundaries. The TO region is represented by the red ellipse.
REGION A CALCULATION
STEP 1: Region A donates 20 persons to the TO region, while there are a further 60 people in FROM Region A that are not donated to the TO region. Therefore the ratio of FROM region A is 20 / 80, or 0.25.
STEP 2: The next step is to look at the value that is being donated from Region A compared to the total value of the TO region (ie 80 persons comprising 20 from Region A + 20 from Region B + 40 from Region C). Region A donates 20 persons, and the total population is 80. So in this case the ratio is 20 / 80, or 0.25.
STEP 3: Region A's component score is then calculated by multiplying the TO and FROM score (0.25 x 0.25) giving Region A a component score of 0.0625.
The same process is then applied to FROM Regions B and C.
REGION B CALCULATION
Region B donates 20 persons with a further 80 persons in the remainder of the FROM region. Therefore its ratio is 20 / 100 or 0.2. Region B donates 20 persons and the total population of the TO region is 80 so the ratio is 20 / 80 or 0.25. Region B's component score is therefore 0.2 x 0.25 or 0.05.
REGION C CALCULATION
Again Region C donates 40 persons with another 60 in the remainder of FROM Region C. The ratio is 40 / 100 or 0.4. The 40 persons donated are then compared against the total population of the TO region of 80, so the ratio is 40 / 80 or 0.5. This results in the component score for From Region C being 0.4 x 0.5 or 0.2.
SUMMING COMPONENT SCORES
The final step is to add the three component scores. In this case:
The final result is that the TO region in this example would have a quality indicator score of 0.3125, a score that the ABS would regard as being poor, meaning that caution would have to be used when using the results of data converted to the TO region.
The textual descriptions and the associated definitions that will be supplied for each TO region in a correspondence are as follows.
Acceptable (0.75 to 0.9)– The ABS expects that for this TO region the correspondence will convert data to a reasonable degree of accuracy, though caution needs to be applied as the quality of the converted data will vary and may differ from the actual characteristics of the geographic regions involved.
Poor (Less than 0.75) – The ABS expects that for this TO region there is a high likelihood the correspondence will not convert data accurately and that the converted data should be used with caution as it may not reflect the actual characteristics of many of the geographic regions involved.
Overall Quality Indicator
An overall quality indicator is given to each correspondence. The aim of this is to provide users with a reasonable idea of how well the correspondence will convert data across the whole of the correspondence.
The overall quality indicator is derived from multiplying the population of each TO region with that TO regions quality indicator score, based on the methodology described above. The values produced by this multiplication for each TO region are then added together. This aggregated value is then divided by the total population of the TO regions. This will return a result similar to the individual quality indicator scores. Similar textual descriptions are then applied.
Acceptable – The ABS expects that the correspondence will convert data overall to a reasonable degree of accuracy, though caution needs to be applied as the quality of the converted data will vary and may differ in parts from the actual characteristics of the geographic regions involved.
Poor – The ABS expects there is a high likelihood the correspondence will not convert data overall accurately and that the converted data should be used with caution as it may not reflect the actual characteristics of many of the geographic regions involved.
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