Australian Bureau of Statistics
4442.0 - Family Characteristics, Australia, 2009-10
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 27/05/2011
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3 For all topics, information on labour force characteristics, education, income and other demographics are also available.
4 Data from the Family Characteristics topic are presented in this publication. Data for other MPHS topics collected in 2009-10 will be released in separate publications.
5 The Family Characteristics topic has been collected before, in 1982, 1992, 1997, 2003 and in 2006-07. A full list of data items available for the FCS is available from the ABS website <www.abs.gov.au>.
6 The publication Labour Force, Australia (cat. no. 6202.0) contains information about survey and sample design, scope, coverage and population benchmarks relevant to the MPS, and consequently the MPHS. This publication contains definitions of demographic and labour force characteristics, and information about telephone interviewing.
7 The scope of the 2009-10 Family Characteristics Survey (FCS) included all usual residents in private dwellings, except:
8 The survey was conducted in both urban and rural areas in all states and territories, but excluded people living in very remote parts of Australia. This is expected to have only a minor impact on any aggregate estimates that are produced for individual states and territories, with the exception of the Northern Territory where people living in very remote areas account for around 24% of the population.
9 Coverage rules are applied to ensure that each person is associated with only one dwelling and hence has only one chance of selection in the survey. See Labour Force, Australia (cat. no. 6202.0) for more details.
10 ABS interviewers conducted personal interviews by either telephone or at selected dwellings, from July 2009 to June 2010. Each month a sample of dwellings were selected for the MPHS from the responding households in the last rotation group for the MPS. In these dwellings, after the MPS had been fully completed for each person, a usual resident aged 15 years and over was selected at random and asked the additional MPHS questions in a personal interview. Information was collected using Computer Assisted Interviewing (CAI), whereby responses are recorded directly onto an electronic questionnaire in a notebook computer.
11 The FCS collected information from the randomly selected person about the household and about every person in the household, including all children in the household. There were 35,700 person records for the survey.
12 Where the randomly selected respondent was aged 15-17 years, and a parent/guardian or other responsible adult aged 18 years and over was resident in the household, permission was sought from the parent or other adult to interview the young person. Regardless of whether permission was granted, details for Family Characteristics and household income (excluding the income of the selected person) were collected from the parent or other adult.
13 The survey collected information about parent-child relationships beyond the usual residence of the child. The survey collected information about resident children aged 0-17 years in the household who had a natural parent living in another household. In addition, the survey identified whether respondents were parents who had natural children aged 0-17 years living elsewhere with the child's other natural parent.
WEIGHTING, BENCHMARKING AND ESTIMATION
14 Weighting is the process of adjusting results from a sample survey to infer results for the total in-scope population. To do this, a 'weight' is allocated to each covered sample unit (i.e. a person, a family or a household). The weight is a value which indicates how many population units are represented by the sample unit.
15 The first step in calculating weights for each unit is to assign an initial weight, which is 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).
16 The initial weights were calibrated to align with independent estimates of the population of interest, referred to as 'benchmarks' in designated categories of sex by age by state or territory and part of state or territory. 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 groups of persons which may occur due to either the random nature of sampling or non-response.
17 The 2009-10 Family Characteristics data were benchmarked to the Estimated Resident Population (ERP) in each state and territory, excluding the ERP living in very remote areas of Australia, at 31st March 2010. The ERP estimates were based on results from the 2006 Census of Population and Housing. Therefore the estimates from this survey do not (and are not intended to) match estimates for the total Australian resident population (which include persons and households living in non-private dwellings, such as hotels and boarding houses, and in very remote parts of Australia) from other ABS sources.
18 The survey estimates conform to person benchmarks by State, part-of-State, age and sex, and to household benchmarks by State, part-of-State and household composition (number of adults and children usually resident in the household). These benchmark variables are the same as those used in the 1997, 2003 and 2006-07 Family Characteristics surveys. The only change has been in relation to age groups for which some collapsing was required for each collection. The impact of this change on estimates not involving age is minimal.
19 Survey estimates (e.g. counts of persons, families or households) are obtained by summing the relevant weight (for persons, families or households) with the characteristic of interest.
RELIABILITY OF ESTIMATES
20 All sample surveys are subject to error which can be broadly categorised as either sampling error or non-sampling error. Sampling error occurs because only a small proportion of the total population is used to produce estimates that represent the whole population. Sampling error can be reliably measured as it is calculated based on the scientific methods used to design surveys. Non-sampling errors occur when survey processes work less effectively than intended. For example, some persons selected for the survey may not respond (non-response); some survey questions may not be clearly understood by the respondent; and occasionally errors can be made in processing data from the survey.
21 Sampling error is the difference between the published estimates, derived from a sample of persons, and the value that would have been produced if all persons in scope of the survey had been included. Sampling error is measured for this survey by relative standard errors (RSEs). For more information refer to the Technical Note.
22 One of the main sources of non-sampling error is non-response by persons selected in the survey. Non-response can affect the reliability of results and can introduce bias. The magnitude of any bias depends upon the level of non-response and the extent of the difference between the characteristics of those people who responded to the survey and those who did not.
23 To reduce the level and impact of non-response, the following methods were adopted in this survey:
24 Every effort was made to minimise other non-sampling error by careful design and testing of questionnaires, intensive training and supervision of interviewers, and extensive editing and quality control procedures at all stages of data processing.
25 An advantage of the CAI technology used in conducting interviews for this survey is that it potentially reduces non-sampling errors by enabling edits to be applied as the data are being collected. The interviewer is alerted immediately if information entered into the computer is either outside the permitted range for that question, or contradictory to information previously recorded during the interview. These edits allow the interviewer to query respondents and resolve issues during the interview. CAI sequencing of questions is also automated such that respondents are asked only relevant questions and only in the appropriate sequence, eliminating interviewer sequencing errors.
26 Family Surveys were conducted by the ABS in 1982 and 1992, and the Family Characteristics Survey (FCS) was previously conducted in 1997, 2003 and 2006-07. The Family Surveys, and to a lesser extent the 1997 FCS, differed from the 2003 and 2006-07 FCS in some areas. Nevertheless, these differences do not preclude useful comparisons between them for certain data items. Some data from the 1997, 2003 and 2006-07 surveys have been included in this publication to show changes over time.
27 Changes listed below were made to the content of the FCS between 1997 and 2003, and between 2003, 2006-07 and 2009-10. These changes should be noted when making comparisons over time.
FAMILY CODING PRACTICES
28 Data items such as 'family composition' in household surveys are based on initial information gathered about the members of the household and their relationships to each other. Family coding is the process of allocating household members to families, where appropriate, based on their spousal, parent-child, and other familial relationships to other members of the household. All children aged 0-14 years are assigned a parent or nominal parent, for example a grandchild living with only his/her grandparents will have the grandparents allocated as nominal parents.
29 The family topics in the 2006-07 FCTS and 2009-10 FCS are designed to capture more accurate information about the composition of families than that collected in other ABS surveys. In 2006-07 and 2009-10, as was the case in 2003, a number of populations and data items have been modified to more accurately classify persons and families where there was a parent/guardian and child/ward relationship. Prior to the 2003 FCS, children aged 15-17 years whose relationship fell outside the standard parent-child classifications (e.g. grandchildren living with grandparents, children living with other related or unrelated adults in a guardian-ward relationship) were classified as 'other related individuals' or 'unrelated individuals'.
30 For example, in the 1997 FCS a 15-17 year old child living with his or her grandparents would have resulted in the grandparents being coded to 'couple family without children' and the child would be an 'other related individual'. For the 2003, 2006-07 and 2009-10 surveys, the family classification allows for inclusion of people with this relationship in the same family. For the example outlined above, the family would be classified as a 'couple family with children'.
31 The ABS plans to repeat the Family Characteristics topic three yearly as part of MPHS. It will next be collected in 2012-13, along with the Family Transitions and History topic which is collected 6 yearly.
32 ABS surveys draw extensively on information provided by individuals, businesses, governments 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.
PRODUCTS AND SERVICES
Publication data cubes
33 Data cubes of all tables related to this publication in Excel spreadsheet format can be found on the ABS website (from the download tab of this publication). The spreadsheets present tables of estimates, proportions and the corresponding relative standard errors (RSEs).
Data item list
34 A full list of data items is also available from the ABS website (see the Downloads tab for cat. no. 4442.0).
35 Selected tables at the state and territory level will be available for download as Excel spreadsheets from the ABS website. These tables will be customised depending on the size of the sampling error.
36 For users who wish to undertake more detailed analysis of the survey data, microdata will be available in the form of a confidentialised unit record file (CURF) (cat. no. 4442.0.55.001). The CURF will only be available via the Remote Access Data Laboratory (RADL), which is a secure Internet-based data query service. Technical information describing the content and use of the CURF will be available in a Technical Manual (cat. no. 4442.0.55.002).
37 A full range of up-to-date information about the availability of ABS CURFs and about applying for access to CURFs is available via the ABS website (see Services, Confidentialised Unit Record Files). Inquiries to the ABS Microdata Access Strategies Section should be made by e-mail: email@example.com, or telephone (02) 6252 7714.
Special data services
38 The ABS offers specialist consultancy services to assist clients with more complex statistical information needs. Clients may wish to have the unit record data analysed according to their own needs, or require tailored tables incorporating data items and populations as requested by them. Tables and other analytical outputs can be made available electronically or in printed form. However, as the level of detail or disaggregation increases with detailed requests, the number of contributors to data cells decreases. This may result in some requested information not being able to be released due to confidentiality or sampling variability constraints. All specialist consultancy services attract a service charge, and clients will be provided with a quote before information is supplied. For further information, contact the National Information and Referral Service on 1300 135 070.
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This page last updated 25 February 2015