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USING THE CURF MICRODATA
USE OF WEIGHTS
The survey was conducted on a sample of employees from a sample of employers in Australia, and as such users need to take this into account when deriving estimates from the CURF. Each employee record contains a weight (FINPRSWT), and this weight indicates how many employees in the population are represented by this employee. Where estimates are derived from the CURF, it is essential they are calculated using the weights.
An employee's chance of selection in the survey varied considerably, depending on their employer's state, sector, industry and size. If an employee's survey weight is ignored, then no account will be taken of the employee's chance of selection, and the resulting estimates may be biased.
A number of the weights in the CURF have been slightly modified from the original survey weights for confidentiality reasons. This reweighting process has not resulted in significant changes to the estimates and the statistical validity of the CURF is not affected.
Weekly earnings data items have been perturbed and are expressed as continuous data items (in whole dollars only) on the CURF. Perturbation is a process of slightly altering the reported values to prevent identification of respondents. The distribution of values is not changed significantly through perturbation and the statistical validity of aggregate data is not affected.
HOURS PAID FOR
'Hours paid for' data items were only collected for non-managerial employees. For managerial employees, a value of '0' has been applied to all 'Hours paid for' data items in the CURF. It is therefore important to take this into account when undertaking analysis which includes the 'Hours paid for' data items.
RECONCILIATION OF CURF WITH PREVIOUSLY PUBLISHED DATA
Steps to confidentialise the data made available on the CURF are taken in such a way as to maximise the content of the file while maintaining the confidentiality of respondents. The steps taken to preserve confidentiality include:
As a result, it may not be possible to exactly reconcile all statistics produced from the CURF with previously published statistics. However, these differences are not significant and should not diminish the value of the CURF in analysis.
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