National Social Housing Survey, 2012; Data Quality Statement
Identifying and definitional attributes
|Metadata item type:||Quality Statement|
|Registration status:||AIHW Data Quality Statements, Archived 05/06/2015|
|Quality statement summary:|
The 2012 NSHS collects information from tenants from three social housing programs—PH, CH and SOMIH.
The NSHS provides information on characteristics of tenants, information about their housing histories, their satisfaction with their housing and information about their household’s use of other health and community services.
Lonergan Research was engaged by the AIHW to conduct the 2012 National Social Housing Survey (NSHS). Data were collected via postal and online (self-completion) questionnaire from a randomly selected sample of SOMIH, Public Housing (PH) and Community Housing (CH) tenants. The tenants completing the questionnaires were from all jurisdictions.
Simple random sampling was undertaken for all housing programs except for NSW PH in which stratified sampling was undertaken in order to maximise the chance of obtaining minimum sample size requirements of 342 per Area.
To produce reliable estimates for each housing program, minimum sample sizes were set for each housing program. An additional 4,950 booster sample was allocated to NSW PH (4,300) and NSW CH (650).
The 2012 NSHS sampling and stratification methods were similar to the 2010 and 2007 survey i.e. sample was randomly selected from each jurisdiction’s SOMIH, Public and Community housing tenants.
The larger sampling fraction of the lesser populated states and territories produced a sample that was not proportional to the distribution of the population of social housing tenants across jurisdictions and housing programs. Weighting was applied to ensure that the results relate to the social housing population.
With the exception of ACT, the weighting for the 2012 survey was calculated as the number of households divided by the number of responses for each jurisdiction by housing type by ARIA. For ACT, weights were calculated by the same method by housing type without ARIA.
The Australian Institute of Health and Welfare (AIHW) is a major national agency set up by the Australian Government under the Australian Institute of Health and Welfare Act 1987 to provide reliable, regular and relevant information and statistics on Australia's health and welfare. It is an independent statutory authority established in 1987, governed by a management Board, and accountable to the Australian Parliament through the Health and Ageing portfolio.
The AIHW aims to improve the health and wellbeing of Australians through better health and welfare information and statistics. It collects and reports information on a wide range of topics and issues, ranging from health and welfare expenditure, hospitals, disease and injury, and mental health, to ageing, homelessness, disability and child protection.
The Institute also plays a role in developing and maintaining national metadata standards. This work contributes to improving the quality and consistency of national health and welfare statistics. The Institute works closely with governments and non-government organisations to achieve greater adherence to these standards in administrative data collections to promote national consistency and comparability of data and reporting.
One of the main functions of the AIHW is to work with the states and territories to improve the quality of administrative data and, where possible, to compile national datasets based on data from each jurisdiction, to analyse these datasets and disseminate information and statistics.
The Australian Institute of Health and Welfare Act 1987, in conjunction with compliance to the Privacy Act 1988, (Cth) ensures that the data collections managed by the AIHW are kept securely and under the strictest conditions with respect to privacy and confidentiality.
For further information see the AIHW website www.aihw.gov.au.
Data are not collected annually. Surveys for PH and CH were conducted in 2001, 2003, 2005, 2007, 2010 and 2012. Surveys for SOMIH were conducted in 2005, 2007 and 2012.
The fieldwork for 2012 was conducted from 18 May–27 June for the ACT. For all other jurisdictions, fieldwork was conducted from 25 May–30 July 2012. For 2012, NSHS data are generally collected for the reference period for the last 12 months since May 2011.The first release of data from the 2012 NSHS was on the 28th May 2013.
Published results from the 2012 NSHS are available on the AIHW website, see National Social Housing Survey 2012: national results report and National Social Housing Survey 2012: detailed findings report. Access to the confidentialised unit record file may be requested through the AIHW Ethics Committee.Users can request data not available online or in reports via the Communications, Media and Marketing Unit on (02) 6244 1032 or via email to email@example.com. Requests that take longer than half an hour to compile are charged for on a cost-recovery basis.
Information to aid in interpretation of 2012 NSHS results may be found in the National Social Housing Survey 2012: a summary of national results, as well as future publications.
In addition, the 2012 Technical Report, code book and other supporting documentation will be available on the AIHW website or through METeOR.Metadata and definitions relating to this data source can be found in the National Housing Assistance Data Dictionary (AIHW Cat no. HOU147). Supplementary information can be found in the public rental, SOMIH and community housing collection manuals which are available upon request from the AIHW.
|Relevance:||The 2012 NSHS comprise tenants from public housing, community housing and state owned and managed Indigenous housing. The Indigenous Community Housing (ICH) sector was excluded from the survey. The survey refers to ‘the last 12 months’ - that is, between June 2011 and June 2012. All states and territories participated in the survey if the relevant program operated in their jurisdiction. All remoteness areas were included in the sample. The speed of delivery to, and returns from, more remote locations may have affected the number of responses received from tenants in these areas.|
Some survey respondents did not answer all questions, either because they were unable or unwilling to provide a response. The survey responses for these people were retained in the sample, and the missing values were recorded as not answered. No attempt was made to deduce or impute these missing values.
The accuracy of the outputs from the 2012 NSHS are affected by the response rates across the jurisdictions and at the National level (see response rate tables below).
Overall, 82,175 questionnaires were sent to tenants in PH, CH and SOMIH, of which 13,381 questionnaires were categorised as being complete and useable, representing a response rate for the 2012 survey of 16.3%; considerably lower than the 2010 survey of 38.6%.
A low response rate does not necessarily mean that the results are biased. As long as the non-respondents are not systematically different in terms of how they would have answered the questions, there is no bias. Given the relatively low response rates for this survey, it is likely there is some bias in the estimates. However, it is not possible to identify or estimate any bias without a follow-up of non-respondents.
The 2012 NSHS was designed to achieve minimum sample requirements for each housing program which in turn controlled the level of sampling error present in the estimates.
The measure used to indicate reliability of individual estimates reported in 2012 was the relative standard error (RSE). Only estimates with RSEs of less than 25% are considered sufficiently reliable for most purposes. Results subject to RSEs of between 25% and 50% should be considered with caution and those with relative standard errors greater than 50% should be considered as unreliable for most practical purposes.
In addition to sampling errors, the estimates are subject to non-sampling errors. These can arise from errors in reporting of responses (for example, failure of respondents’ memories, incorrect completion of the survey form), the unwillingness of respondents to reveal their true responses and the higher levels of non-response from certain subgroups of the population.
Also, given the relatively low response rates for this survey, it is likely there is some non-response bias in the estimates. However, it is not possible to identify or estimate any bias without a follow-up of non-respondents.
Finally, there also exists the possibility of data capture and coding errors in the NSHS dataset.The survey findings are also based on self-reported data.
In 2010, the data collected for public and community housing excluded the ACT as this jurisdiction had undertaken its own collection. Trend data should therefore be interpreted with caution.
Comparisons between jurisdictions’ data should be undertaken with caution due to differences in response rates which have potentially lead to differences in non-sampling error between collections.
Surveys in this series commenced in 2001. Over time, modifications have been made to the survey’s methodology and questionnaire design. The sample design and the questionnaire of the 2012 survey differs in a number of important respects from previous versions of the survey which means that caution is required if comparing estimates between surveys.
Caution should be used if comparing 2012 results to 2010 due to the substantially lower response rates in 2012. The decrease in response rates in 2012 may have increased the survey’s exposure to non-response bias compared to previous surveys and results should therefore be interpreted with caution.Comparisons of estimates of customer satisfaction between 2010 and 2012 should be avoided due to changes in the methodology of the survey and the levels of sampling error associated with these figures.
Source and reference attributes
|Submitting organisation:||The Australian Institute of Health and Welfare|
|Related metadata references:|
Has been superseded by National Social Housing Survey, 2014; Data Quality Statement AIHW Data Quality Statements, Archived 06/01/2017