4715.0.30.003 - Microdata: Australian Aboriginal and Torres Strait Islander Health Survey, Core Content - Risk Factors and Selected Health Conditions, 2012-13 
Quality Declaration
Quality Declaration ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 28/07/2015 First Issue
Page tools:
 Print Page
 Print All
| ||||||||||||||||||||||||||||||||||||
|
USING THE TABLEBUILDER ...and the Summation Options. The following table shows the responses for 'Systolic Blood Pressure' by 'Sex of person' using the version in the Person folder. The continuous values of the data item are contained in the 'A valid response was recorded' row. If the actual continuous values are to be displayed then it is necessary to use the Summation Option version and create a range for them. Here is the same table with a range applied for the continuous values of 'Systolic Blood Pressure (mmHG)' (called SysExample). Note that the numbers of respondents for the other responses 'Not applicable', 'Valid reading not obtained' and 'Not measured' no longer contribute to the table. Any special codes for continuous data items are listed in the Data Item List. Continuous items can be used to create custom categories in 'My Custom Data' by first ranging the item. For example, to create five year age groupings for 'Age first told had diabetes or high sugar levels' this can be done by ranging the item with a five year increments from Summation Options. However to deviate from groupings of equal increments, this must be done in 'My Custom Data'. As age is a continuous item, for deviations from equal increments, it must first be ranged (for example in one year increments) and then this ranged item can be grouped under the 'My Custom Data' tab to form unique age categories. For more information see the 'My Custom Data' section of the User Manual: TableBuilder, Jun 2013 (cat. no. 1406.0.55.005). CONFIDENTIALITY FEATURES IN TABLEBUILDER In accordance with the Census and Statistics Act 1905, all the data in TableBuilder are subjected to a confidentiality process before release. This confidentiality process is undertaken to avoid releasing information that may allow the identification of particular individuals, families, households, dwellings or businesses. Processes used in TableBuilder to confidentialise records include the following: Perturbation Effects 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. These adjustments have a negligible impact on the underlying pattern of the statistics. The introduction of these random adjustments result in tables not adding up. While some datasets apply a technique called additivity to give internally consistent results, additivity has not been implemented on this TableBuilder. As a result, randomly adjusted individual cells will be consistent across tables, but the totals in any table will not be the sum of the individual cell values. The size of the difference between summed cells and the relevant total will generally be very small. Please be aware that the effects of perturbing the data may result in components being larger than their totals. This includes determining proportions. Table suppression Some tables generated within TableBuilder may contain a substantial proportion of very low counts within cells (excluding cells that have counts of zero). When this occurs, all values within the table are suppressed in order to preserve confidentiality. The following error message below is displayed at the bottom of the table when table suppression has occurred. ERROR: The table has been suppressed as it is too sparse ERROR: table cell values have been suppressed Field exclusion rules Certain groups of similar variables are restricted from being used together in a table. These restrictions are referred to as field exclusion rules, and are in place in order to protect confidentiality. The collections of similar variables restricted in this way are called field exclusion groups. For the Australian Aboriginal and Torres Strait Islander Health Survey there is one field exclusion group. This consists of the 2011 geographical and Socio-Economic Indexes for Areas (SEIFA) data items (see below for items). Only one data item from this group may be used in a single table. The geographic exception to this is the State or Territory item, which can be used in addition to one item from this group. Items included in the field exclusion group are: 2011 Geographic Items
2011 SEIFA Items
WEIGHT VARIABLES There are two weight variables visible on the TableBuilder file under Summation Options categories:
TableBuilder will apply 'Persons (Benchmarked weight)' by default. Using Weights The AATSIHS is a sample survey. To produce estimates for the in-scope population you must use weight fields in your tables. The weight fields are listed below. In TableBuilder they can be found under the Summation Options category in the left hand pane under the applicable level. If you do not select a weight field, TableBuilder will use 'Persons (Benchmarked weight)' by default. This will give you estimates of the number of persons. To produce estimates for AATSIHS selected persons who participated in the National Aboriginal and Torres Strait Islander Health Measures Survey (NATSIHMS), the 'Biomedical persons (Benchmarked weight)' located on the Biomedical level must be used. When using a Weight/Summation from a level that is different to that of the variables in the table please be careful in interpreting the results.
Note that the Biomedical level also contains non-biomedical participant records, however their biomedical weight is set to 0 so they will not contribute to estimates when the Biomedical persons (Benchmarked weight) is used. However, if the Persons (Benchmarked weight) is used with biomedical data items then these non-participants will contribute to estimates. When using biomedical variables in conjunction with other variables on the biomedical level or with variables from other levels, the Biomedical persons (Benchmarked weight) should be used. For example, a table of reported fasting status using the 'Persons (Benchmarked weight)' will show the fasting status for the entire Australian Aboriginal and Torres Strait Islander Health Survey. Note that the 'Not applicable' persons include those people who did not participate in the NATSIHMS. The population for this table presents the weighted estimates for the Aboriginal and Torres Strait Islander population aged 2 years and over. The same table using the 'Biomedical persons (Benchmarked weight)' will show the fasting status for only persons who participated in the NATSIHMS. Note that in this case, no-one is in the 'Not applicable' category. People who did not participate in the biomedical component do not have a biomedical person weight and therefore do not contribute to the table when this weight is used. The biomedical population now presents weighted estimates for the Aboriginal and Torres Strait Islander population aged 18 years and over. MEANS AND MEDIANS Means, medians and sums of continuous data items are calculated at the level of the continuous data item. A weight is automatically applied from a weight allocated behind the scenes to the level of the variable. For all levels, other than Household, Persons in household and Biomedical levels, a person weight has been applied to each record (e.g. physical activity record) on the level based on the weight allocated to selected persons on the Person level. The biomedical weight has been applied to each biomedical participant on the Biomedical level. No weight has been applied to the Household or Persons in household levels due to there not being a household weight produced, but neither level has continuous items located on them which require a weight for calculations. Due to current functionality of the software, a weight from another level cannot be brought into such calculations. The "subject" of means, medians and sums calculated in TableBuilder is therefore the statistical unit associated with the level of the database on which the continuous data item is stored. For example, the mean of the "Total minutes spent doing physical activity type that day (5-17)" data item at the Child 5-17 Years Physical Activity Detailed (NR Only) level would give the mean total minutes of physical activity by physical activity type and across 3 days while the mean of the "Total minutes doing mod to vig physical activity that day" at the Child 5-17 Years Physical Activity Detailed (NR Only) level would give the mean total minutes for physical activity across 3 days. The weights used for these calculations are not visible but are referenced in the 'Weighted by' statement with continuous variables, as per: ITEMS LOCATED ON MULTIPLE LEVELS Where items are available on more than one level, an additional number is added to the label to indicate the level version. For example a (1) indicates it's a Household level version, a (2) indicates a Persons in household level version, a (3) indicates a Person level version, and so on. These are identified in the Data item list labelling as well as the item in TableBuilder. The numbering is based on the ordering of levels found in the File Structure page of this product. Care should be used to ensure the correct version of the item is used, particularly with regards to demographic items located on both the Persons in household and Person levels. See below for more details. PERSONS IN HOUSEHOLD LEVEL VERSUS PERSON LEVEL VARIABLES The Persons in Household level contains data for every person in the household while the Persons level only contains data for the selected persons. Both levels are children of the Household level - that is, they are siblings and are not linked by person but by household. This means that there is a many-to-many link between records at these levels (persons on the Person level are linked to all the people in their household on the Persons in household level). When summing the Person weight (which is stored at the Person level) the meaning of the estimates produced when disaggregating by another data item at the Person level will not be the same as the meaning of the estimates produced when disaggregating by a data item at the Persons in Household level. For example, disaggregating by Sex and Marital status at the Person level will produce estimates of the type "Number of persons who are Male and Married". These estimates will be additive (aside from the effects of perturbation) as shown below. On the other hand, disaggregating by Sex and Marital status at the Persons in Household level, and using the 'Persons (Benchmarked weight)' from the Person level, will produce estimates of the type "Number of persons in households containing one or more persons who are Male and Married". These estimates will usually not be additive as shown below. Document Selection These documents will be presented in a new window.
|
|||||||||||||||||||||||||||||||||||
