### Reliability of estimates

As the survey was conducted on a sample of households in Australia, it is important to take account of the method of sample selection when deriving estimates from the detailed microdata. This is important as a person's chance of selection in the survey varied depending on the state or territory in which the person lived. If these chances of selection are not accounted for by use of appropriate weights, the results could be biased.

Each person record has a main weight (FINWTPC). This weight indicates how many population units are represented by the sample unit. When producing estimates of sub-populations from the detailed microdata, it is essential that they are calculated by adding the weights of persons in each category and not just by counting the sample number in each category. If each person’s weight were to be ignored when analysing the data to draw inferences about the population, then no account would be taken of a person's chance of selection or of different response rates across population groups, with the result that the estimates produced could be biased. The application of weights ensures that estimates will conform to an independently estimated distribution of the population by age, by sex, etc. rather than to the distributions within the sample itself.

It is also important to calculate a measure of sampling error for each estimate. Sampling error occurs because only part of the population is surveyed to represent the whole population. Sampling error should be considered when interpreting estimates as this gives an indication of accuracy and reflects the importance that can be placed on interpretations using the estimate. Measures of sampling error include standard error (SE), relative standard error (RSE) and margin of errors (MoE). These measures of sampling error can be estimated using the replicate weights. The replicate weight variables provided on the microdata are labelled WPC01XX, where XX represents the number of the given replicate group. The exact number of replicates will vary depending on the survey but will generally be 30, 60 or 200 replicate groups. As an example, for survey microdata with 30 replicate groups, you will find 30 person replicate weight variables labelled WPC0101 to WPC0130.