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SCOPE OF THE SURVEY
5 Only people who were usual residents of private dwellings in Australia were covered by the GSS. Private dwellings are houses, flats, home units and any other structures used as private places of residence at the time of the survey. People who usually reside in non-private dwellings such as hotels, motels, hostels, hospitals and short-stay caravan parks were not included in the survey. Usual residents are those who usually live in a particular dwelling and regard it as their own or main home. Visitors to private dwellings are not included in the interview for that dwelling. However, if they are a usual resident of another dwelling that is in the scope of the survey, they have a chance of being selected in the survey or, if not selected, they will be represented by similar persons who are selected in the survey.
6 The GSS was conducted in both urban and rural areas in all states and territories, except for very remote parts of Australia and discrete Indigenous communities. This exclusion is unlikely to impact on national estimates, and will only have a minor impact on any aggregate estimates that are produced for individual states and territories, except the Northern Territory where the excluded population accounts for over 20% of persons.
7 The Australian population at June 2014, after exclusion of people living in non-private dwellings, very remote areas of Australia and discrete Aboriginal and Torres Strait Islander communities was 22,828,900, of which 18,463,700 were aged 15 years and over.
8 The following people were excluded from resident population estimates used to benchmark the survey results, and were not interviewed:
9 The GSS was designed to provide reliable estimates at the national level and for each State and Territory. The sample was therefore spread across the states and territories in order to produce estimates that have a relative standard error (RSE) of no greater than 10% for characteristics that are relatively common in the national population (that at least 10% of the population would possess).
10 For the 2014 cycle, in order to be consistent with the aim of exploring the relative outcomes of people more vulnerable to socio-economic disadvantage, the sampling methodology was adapted to target sample from low socio-economic areas. People in these areas had a higher probability of being selected in the sample. Households were then randomly selected from each selected area to participate in the survey.
11 The initial sample for the survey consisted of approximately 18,574 private dwellings. This number was reduced to approximately 16,145 dwellings due to the loss of households which had no residents in scope for the survey and where dwellings proved to be vacant, under construction or derelict. Of the eligible dwellings, 80.1% responded fully (or adequately) which yielded a total sample from the survey of 12,932 dwellings.
12 Some survey respondents provided most of the required information, but were unable or unwilling to provide a response to certain data items. The records for these persons were retained in the sample and the missing values were recorded as 'don't know or not stated'. No attempt was made to deduce or impute for these missing values. Details of missing values for data items are presented in paragraph 31.
13 ABS Interviewers conducted personal interviews using a Computer Assisted Interviewing (CAI) questionnaire at selected dwellings during the period March to June 2014. CAI involves the use of a notebook computer to record, store, manipulate and transmit the data collected during interviews.
14 Much of the detail obtained from the GSS was provided by one person aged 15 years or over, randomly selected from each participating household. The random selection of this person was made once basic information had been obtained about all household members. Some financial and housing items collected in the GSS required the selected person to answer on behalf of other members of the household. In some cases, particularly where household information was not known by the selected person, a spokesperson for the household was nominated to provide household information.
WEIGHTING, BENCHMARKING AND ESTIMATION
15 Weighting is the process of adjusting results from a sample survey to infer results for the total in-scope population whether that be persons or households. To do this, a 'weight' is allocated to each sample unit i.e. a person or a household. The weight is a value which indicates how many population units are represented by the sample unit.
16 The first step in calculating weights for each person or household is to assign an initial weight, which is equal to the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (that is, they represent 600 people).
17 The initial weights are then calibrated to align with independent estimates of the population of interest, referred to as 'benchmarks'. Weights calibrated against population benchmarks ensure that the survey estimates conform to the independently estimated distribution of the population rather than to the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of persons which may occur due to either the random nature of sampling or non-response.
18 The GSS was benchmarked to the in scope estimated resident population (ERP) and the estimated number of households in the population. The 2014 GSS used population and household benchmarks based on the 2011 Census.
19 Given that the GSS did some targeting towards low socio-economic areas, further analysis was undertaken to ascertain whether benchmark variables, in addition to geography, age, and sex, should be incorporated into the weighting strategy. Analysis showed that the standard weighting approach did not adequately compensate for differential undercoverage in the 2014 GSS sample for SEIFA, when compared to other ABS surveys. As this variable was considered to have possible association with social characteristics, an additional benchmark was incorporated into the weighting process.
20 The benchmarks used in the calibration of final weights for the 2014 GSS were:
21 Survey estimates of counts of persons are obtained by summing the weights of persons or households with the characteristic of interest. Estimates for means, such as mean age of persons, are obtained by summing the weights of persons in each category (e.g. individual ages), multiplying by the value for each category, aggregating the results across categories, then dividing by the sum of the weights for all persons.
22 The majority of estimates shown in this publication are based on benchmarked person weights. The estimates in Table 15 however, are based on benchmarked household weights.
23 The estimates in this publication are based on information collected from March to June 2014, and due to seasonal effects they may not be fully representative of other time periods in the year. For example, the GSS asked standard ABS questions on labour force status to determine whether a person was employed. Employment is subject to seasonal variation through the year. Therefore, the GSS results for employment could have differed if the GSS had been conducted over the whole year or in a different part of the year.
EQUIVALISED GROSS HOUSEHOLD INCOME
24 The economic wellbeing of individuals is largely determined by their command over economic resources. People's income and reserves of wealth provide access to many of the goods and services consumed in daily life. The amount of income to which they have access is an important component of these resources. And while income is usually received by individuals, it is normally shared between partners in a couple relationship and with any dependent children. To a lesser degree, there may be sharing with other members of the household. Even when there is no transfer of income between members of a household, nor provision of free or cheap accommodation, members are still likely to benefit from the economies of scale that arise from the sharing of dwellings. Therefore, the income measures shown in this publication relate to household income.
25 Gross household income can be used as an indicator of whether a person has a relatively high or low level of economic wellbeing. However, larger households normally require a greater level of income to maintain the same standard of living as smaller households, and the needs of adults are normally greater than the needs of children. Equivalised household income estimates are estimates which have been adjusted by equivalence factors which standardise the income estimates with respect to household size and composition. Therefore, estimates of equivalised gross household income are used in this publication as a more relevant indicator of relative economic wellbeing than non-equivalised household income.
26 Equivalised household income is derived by calculating an equivalence factor according to an equivalence scale, and then dividing household income by the factor. In this publication the 'modified OECD' equivalence scale is used. The equivalence factor derived using this scale is built up by allocating points to each person in a household. Taking the first adult in the household as having a weight of 1 point, each additional person who is 15 years or older is allocated 0.5 points, and each child under the age of 15 years is allocated 0.3 points. Equivalised gross household income is derived by dividing total gross household income by a factor equal to the sum of the equivalence points allocated to the household members. The equivalised gross household income of a lone person is the same as its unequivalised gross household income. The equivalised gross household income of a household comprising more than one person lies between the total value and the per capita value of its unequivalised gross household income.
INTERPRETATION OF RESULTS
27 Care has been taken to ensure that the results of this survey are as accurate as possible. All interviews were conducted by trained ABS Interviewers. Extensive reference material was developed for use in the field enumeration and intensive training was provided to interviewers in both classroom and on-the-job environments. There remain, however, other factors which may have affected the reliability of results, and for which no specific adjustments can be made. The following factors should be considered when interpreting these estimates:
28 The Survey of Mental Health and Wellbeing (SMHWB) is the best ABS source of information on the prevalence of mental health conditions in Australians aged 16-85 years. The SMHWB is different from other surveys collecting mental health data because it does not rely on self-reporting. Rather, it uses diagnostic assessment criteria to assess the lifetime, and 12-month prevalence, of selected mental disorders through the measurement of symptoms and their impact on day to day activities. The survey was based on a widely used international survey instrument (World Mental Health Survey Initiative version of the World Health Organization Composite International Diagnostic Interview, version 3.0), but tailored for the Australian context.
29 Other surveys, including the GSS, rely on self-reporting of diagnosed mental health conditions. While not providing a prevalence measure, information obtained from these surveys is valuable for comparing population characteristics of people with/without a mental health condition within the particular survey in which it has been used.
30 The voluntary work estimates for 2014 presented in the survey, exclude those persons who were compelled to do voluntary work because of employment or study commitments, for example, work for the dole. For further information on voluntary work, and for comparisons over time, refer to the publication Voluntary Work, Australia (cat. no. 4441.0).
31 For a number of GSS data items, some respondents were unwilling or unable to provide the required information. No imputation was undertaken for this missing information. Where responses for a particular data item were missing for a person or household they were recorded in a 'not known or not stated' category for that data item. These 'not known or not stated' categories are not shown in the publication tables. However, the person or household has been included in the total for most data items. Below is a table showing the number and proportion of missing values for key GSS data items.
KEY GSS DATA ITEMS WITH A 'NOT KNOWN OR NOT STATED' CATEGORY
* estimate has a relative standard error of 25% to 50% and should be used with caution
** estimate has a relative standard error greater than 50% and is considered too unreliable for general use
*** Nil or rounded to zero (including null cells)
(a) Also see paragraph 32
32 For persons or households reporting nil or negative total income, or where the income amount was unknown, the principal source of income has been classified as 'undefined'. The principal source of personal income was 'undefined' for an estimated 2.7 million persons (15%). An estimated 345,000 persons lived in households where the principal source of household income was 'undefined' (2%).
33 Occupation data were classified according to the Australian ANZSCO - Australian and New Zealand Standard Classification of Occupations, 2013, Version 1.2 (cat. no. 1220.0).
34 Country of birth data were classified according to the Standard Australian Classification of Countries (SACC), 2011 (cat. no. 1269.0).
35 Area data (Capital city, Balance of state/territory; Remoteness areas) are classified according to the Australian Statistical Geography Standard (ASGS).
36 Education data were classified according to the Australian Standard Classification of Education, 2001 (cat. no. 1272.0).
COMPARABILITY WITH 2010 GSS
37 Selected summary results from the 2006 and 2010 GSS are presented in this publication to provide comparisons over time. The statistical significance of differences in estimates between 2010 and 2014 have been investigated. For the 2014 estimates in Table 1 where the difference, when compared to the 2010 rate is statistically significant, a cell comment has been included. While the content and data collection were largely the same in both collections, the sample design and weighting procedures were not. Some differences are noted below.
38 The GSS is designed to collect information for a core set of topics in each cycle, to allow analysis of changes over time, and a cyclical component to collect additional information. Approximately 80% of the content of the 2010 GSS was repeated in the 2014 GSS. Differences in content between the surveys include the cyclical component of the GSS and some new content. A detailed voluntary work module similar to what formed part of the 2006 iteration, was included as part of the cyclical component for the 2014 GSS. This will allow more direct comparison with the 2006 volunteering data. New topics in 2014 included long term health condition, discrimination, visa status, barriers to employment, sexual orientation and parental educational attainment.
39 A full list of the data items from the 2014 GSS are contained in the Data Item List which can be found in the Downloads tab. For published results from the 2010 GSS, refer to General Social Survey: Summary Results, Australia, 2010 (cat. no. 4159.0).
40 Level of highest educational attainment was derived from information on highest year of school completed and level of highest non-school qualification. The derivation process determines which of the 'non-school' or 'school' attainments will be regarded as the highest. Usually the higher ranking attainment is self-evident, but in some cases some secondary education is regarded, for the purposes of obtaining a single measure, as higher than some certificate level attainments. The 2010 GSS treated those respondents who had completed a lower level certificate as having a higher qualification than Year 10. This was different for the 2014 GSS, where Year 10 was treated as having a higher qualification than a lower level certificate.
41 There is a conceptual difference between the 2010 and 2014 GSS in the way that those who had 'No disability or no long term health condition' are derived. In the 2010 GSS, there was no long term health conditions module, so the category 'Has no disability or no long term health conditions' was only derived using the questions in the disability module. In 2014, there was a long term health condition module as well as a disability module, so the appropriate questions across the two modules have been used to derive this category. Conceptually, this means that this particular category for Disability Status should not be compared between the 2010 and 2014 iterations.
42 The Appendix presents comparisons between a number of key GSS data items and similar data items from other ABS sources. Where possible, results from other surveys have been adjusted to the scope and coverage of the GSS (or vice versa). A list of data comparisons can be found in the spreadsheet 'Data Comparability between GSS and Other ABS Sources' in the Downloads tab.
PRODUCTS AND SERVICES
43 Below is information describing the range of data to be made available from the 2014 GSS, both in published form and on request. Products available on the ABS web site are indicated accordingly.
General Social Survey: Summary Results, Australia, 2014 Datacubes
44 The tables released in this product are in spreadsheet format and are available in the Downloads tab of this publication. Estimates, proportions and the related Relative Standard Errors (RSEs) are presented for each table.
General Social Survey: User Guide 2014
45 The GSS User Guide will be released in conjunction with the Confidentialised Unit Record File (CURF). It will provide detailed information about the survey content, methodology and data interpretation. It is expected that the User Guide will be available free-of-charge on the ABS web site in September 2015 (cat. no. 4159.0.55.002).
46 It is expected that a Table Builder and an expanded confidentialised unit record file (CURF) will be produced from the GSS, subject to the approval of the Australian Statistician. The expanded CURF will be available via Remote Access Data Laboratory (RADL) and ABS Data Laboratory (ABSDL), and the Table Builder will be accessible via the ABS website, using a secure log-on portal.
47 Special tabulations of GSS data are available on request. Subject to confidentiality and sampling variability constraints, tabulations can be produced from the survey incorporating data items, populations and geographic areas selected to meet individual requirements. These can be provided in printed or electronic form. All enquiries should be made to the National Information and Referral Service on 1300 135 070.
48 ABS publications draw extensively on information provided freely by individuals, businesses, government and other organisations. Their continued cooperation is very much appreciated; without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.
49 Refer to the Related Information tab of this publication for other ABS publications which may be of interest.
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