6324.0.30.001 - Microdata: Work Related Injuries, 2013-14 Quality Declaration 
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 06/07/2015  First Issue
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The Work-Related Injuries TableBuilder file reads approximately 27,000 confidentialised unit records. Each record holds the person-level data of a respondent to the survey. When analysing data from TableBuilder, person weights are automatically applied to the underlying sample counts to provide survey population estimates. Weights are values that indicate how many population units are represented by the sample unit. They align to independently estimated distributions of the population by age, sex, state/territory, part of state and labour force status.

At the person level the file contains general information about each survey respondent such as their age, sex, country of birth, labour force status, their personal income, the income of the household the person is a member of, as well as details specific to their most recent work-related injury or illness.

It is important to note that all the details on the TableBuilder file relate to a person. This includes household income variables which describe the income of the household in which the person resides, and applies that person's weight only (not a household weight). On this file, household income estimates should be interpreted as 'X number of people live in households with an income of Y' and should not be interpreted as 'X number of households have an income of Y'.


The data items included in the 2013-14 Work-Related Injuries TableBuilder are grouped under broad headings as shown in the image below. A complete data item list can be accessed from the Downloads page of this publication. The population relevant to each data item should be considered when extracting and analysing data. The populations that apply to each data item are shown in the data item list.

File structure showing an overview of the data items available. All items fall under the person level, and are then grouped in folders for populations, demographics, geography, labour force, income, education, WRI data items, and health.