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FILE STRUCTURE AND CONTENT
The COE TableBuilder contains a mandatory field called Reference year to allow for historical analysis. By default this field will be present in any new table as per the image below:
Individual years can be removed from the table using the data item panel by selecting the required year and removing it from the table as per the image below:
However, at least one category (reference period) of the mandatory field must be present in a table for TableBuilder to retrieve data.
The COE TableBuilder contains biennial content, distinguished by odd and even years in the Data items list as per the image below:
When a data item is placed in a table and was not applicable for a particular reference year, TableBuilder will return a "Not applicable" reference. Where data is requested for multiple years for a biennial item, TableBuilder will retrieve data at the applicable reference year and return "Not applicable" for the year that the data item was not collected.
Not Applicable Categories
Most data items included in the TableBuilder file include a 'Not applicable' category. The classification values of these 'Not applicable' categories, where relevant, are shown in the data item list in the Downloads tab. The 'Not applicable' category generally represents the number of people who were not asked a particular question or the number of people excluded from the population for a data item when that data were derived (e.g. Status of employment in second job is not applicable for people without a second job).
The population relevant to each data item should be kept in mind when extracting and analysing data. The actual population count for each data item is equal to the total cumulative frequency minus the 'Not applicable' category.
Generally, some populations can be 'filtered' using other relevant data items. For example, if the population of interest is 'Employees', any data item with that population (excluding the 'Not applicable' category) could be used.
Zero Value Cells
Tables generated from sample surveys will sometimes contain cells with zero values because no respondents that satisfied the parameters of a particular cell in a table were in the survey. This is despite there being people in the general population with those characteristics. This is an example of sampling variability which occurs with all sample surveys. Relative Standard Errors cannot be generated for zero cells.
Availability of median earnings data in TableBuilder
For the Characteristics of Employment survey, median weekly earnings are considered to be a more robust measure of centre for earnings data and have been given more prominence since August 2017.
To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves small random adjustments of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released.
The ABS has tested and implemented a new perturbation process in respect of median earnings data to ensure that both the confidentiality of individuals are maintained, and the integrity of medians is better preserved.
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