Definitions
| Age-standardised rate | Age-standardised rates are used when populations have different age structures (for example, the Aboriginal and Torres Strait Islander population has a younger age structure than the non-Indigenous population) and the topic of the data varies with age (for example, older people are more likely to access chronic disease care). Age differences are adjusted across populations using the Australian Estimated Resident Population at 30 June 2001, in accordance with the agreed principles for direct age-standardisation.1 |
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| Confidence interval | Confidence intervals (CIs) represent the range within which the true population result likely lies, based on a sample, with a specified probability level. Confidence intervals in this report use a 95% level of probability. This means we are 95% confident that the ‘true’ result lies within the range specified by the confidence interval. A larger range is indicative of a larger sampling error (see: sampling error). |
| Gender/Sex | A person's sex depends on their sex characteristics, typically determined by those observed at birth or in infancy. Gender may be informed by an individual’s identity, self-expression, or experience and does not always align with sex characteristics recorded at birth (ABS 2021).2 Currently, most data sources used to inform the Closing the Gap dashboard collect and report on data by sex. However, Australian statistical agencies are starting to introduce methods to collect a person’s gender. Information on how sex and/or gender is collected and reported for each target/indicator is provided within the target/indicator data specifications on the dashboard (where sex/gender is reported). Within the dashboard, the terms “men” and “women” refer to adult males and females, as reported by relevant data sources. |
| Indicator | Indicators are the concepts, experiences, or activities that are being measured, including for each of the targets.
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| Linear regression estimate | Linear regression is a technique used to estimate the relationship between variables by fitting a linear equation to a dataset. In this report it is used to compare the baseline year of data to the current year and assess if there is a change in the data. If there is an improvement, the technique is used to project a value for the target year, which is measured against the value of the target to assess if a target is on track to be met. |
| Measure | For each indicator (see: indicator), there may be one or more measures. Measures allow us to create or locate the right data sets and are a more detailed and concrete understanding of what each indicator means. |
| Percentage points | Percentage points are used to refer to changes and differences between one percentage and another. For example, an increase from 11% to 14% constitutes an increase of three percentage points, calculated from the baseline value. |
| Relative standard error | The relative standard error (RSE) measures the sampling error and is expressed as a percentage of the estimate. Estimates with a low RSE have a low sampling error. Estimates with larger RSEs (between 25% and 50%) should be used with caution. Estimates with RSEs of 50% or more are considered unreliable for most purposes. |
| Sampling error | The variation that is expected when data is collected from a subset of a population – the results will not be perfectly identical to the results obtained from collecting data from an entire group. Larger sampling errors are associated with higher relative standard errors (see: relative standard error) and/or wider confidence intervals (see: confidence intervals). |
| Socio-economic quintiles | In this report, socio-economic status is usually classified according to the ABS Socio-Economic Indexes for Areas (SEIFA): Index of Relative Socio-economic Disadvantage (IRSD), which classifies geographic areas into five ‘quintiles’ - most disadvantaged, second most disadvantaged, middle 20%, second least disadvantaged and least disadvantaged - each representing approximately 20% of geographic areas across Australia.3 |
| Target | Targets are specific and measurable goals for each of the outcome areas. Targets focus on an ‘end point’ and are a way to determine if a desired outcome has been achieved. |
| Trajectory | Trajectories show the direction and speed of change needed from today to meet the target in future. |
| Variability bands | Rates derived from administrative data are not subject to sampling error, but might still be subject to natural random variation, especially for small counts. Variability bands account for this variation and are similar to CIs (see: confidence interval) in that they provide a specified range for an estimate which is very likely (95 times out of 100) to contain the ‘true’ value. |
- For more information on the principles used for the age standardisation in this report, see: AIHW 2011, Principles on the use of direct age-standardisation in administrative data collections: for measuring the gap between Indigenous and non-Indigenous Australians, Cat. no. CSI 12, Canberra. AIHW- Indigenous Australians, principles on the use of direct age standardisation
- ABS 2020, Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables. ABS - Standard sex gender variations sex characteristics and sexual orientation variables
- For more information on socioeconomic quintiles, see: ABS - Socio-Economic Indexes for Areas (SEIFA), Australia methodology