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ANNEX 1 TECHNICAL DETAILS OF THE SURVEY

Background to the survey

The Scottish Social Attitudes ( SSA) survey was launched by ScotCen ⁶ (part of the National Centre for Social Research) in 1999, following the advent of devolution. Based on annual rounds of interviews with 1,600 people drawn using random probability sampling its aims are to facilitate the study of public opinion and inform the development of public policy in Scotland. In this it has similar objectives to the British Social Attitudes ( BSA) survey, which was launched by the National Centre in 1983. While BSA interviews people in Scotland, these are usually too few in any one year to permit separate analysis of public opinion in Scotland (see Park, et al, 2003 for more details of the BSA survey).

SSA is conducted annually and has a modular structure. In any one year it will typically contain four or five modules, each containing 40 questions. Funding for its first two years came from the Economic and Social Research Council while from 2001 onwards different bodies have funded each year's individual modules. These bodies have included the Economic and Social Research Council, the Scottish Executive and various charitable and grant awarding bodies such as the Nuffield and Leverhulme Foundations.

Sample design, fieldwork and response

The data in this report are taken from a module of questions asked in the 2004 Scottish Social Attitudes survey. This survey involved a face-to-face interview with respondents and a self-completion questionnaire, completed by over nine in ten of these people (93%). The numbers completing each stage are shown in Table 1. See Bromley, Curtice and Given (2005) for technical details of the 1999-2003 surveys.

Sample design

The survey was designed to yield a representative sample of adults aged 18 or over living in Scotland. The sample frame was the Postcode Address File ( PAF), a list of postal delivery points compiled by the Post Office. The sample design involved three stages:

1. 84 postcode sectors were selected from a list of all postal sectors in Scotland, with probability proportional to the number of addresses in each sector. Prior to selection the sectors were stratified by region, population density, and percentage of household heads recorded as employers / managers (taken from the 2001 Census). The list was also stratified using the using the Scottish Household Survey ( SHS) six-fold classification of urban and rural areas (see below for a description of this), and sectors within rural and remote categories were over-sampled.
2. In order to boost the number of respondents from remote and rural areas 31 addresses were selected in each sector located within the first three SHS urban-rural classifications (the four cities, to accessible small towns), while 62 addresses were selected from the sectors within the three most rural categories (remote small towns to remote rural areas). The issued sample size is shown in Table 1.
3. Interviewers called at each selected address and identified its eligibility for the survey. Where more than one household was present at an address, all households were listed systematically and one was selected at random using a computer generated random selection table. In all eligible households with more than one adult aged 18 or over, interviewers also had to carry out a random selection of one adult using a similar procedure.

Weighting

Data were weighted to take account of the fact that not all households or individuals had the same probability of selection for the survey. For example, adults living in large households have a lower selection probability than adults who live alone. Weighting was also used to correct the over-sampling of rural addresses. All the percentages presented in this report are based on weighted data, the unweighted sample sizes are shown in the tables.

Fieldwork

Fieldwork ran between July and December (with 77% completed by the end of September). An advance letter was sent to all addresses and was followed up by a personal visit from a Scottish Centre for Social Research interviewer. All interviewers attended a one day briefing conference prior to starting work.

Interviews were conducted using face-to-face computer-assisted interviewing (a process which involves the use of a laptop computer, with questions appearing on screen and interviewers directly entering respondents' answers into the computer). All respondents were asked to fill in a self-completion questionnaire which was either collected by the interviewer or returned by post. The next table summarises the response rate and the numbers completing the self-completion in 2004.

Table 1 - 2004 Scottish Social Attitudes survey response

Notes to table

¹This includes addresses identified by interviewers during fieldwork.

²This includes empty / derelict addresses, holiday homes, businesses and institutions.

³Refusals include refusals prior to selection of an individual, refusals to the office, refusal by the selected person, 'proxy' refusals made by someone on behalf of the respondent and broken appointments after which a respondent could not be re-contacted.

⁴Non-contacts comprise households where no one was contacted after at least 4 calls and those where the selected person could not be contacted.

⁵'Unknown eligibility' includes cases where the address could not be located, where it could not be determined if an address was a residence and where it could not be determined if an address was occupied or not.

Analysis variables

A number of standard analyses have been used in the tables in this report. Most of the analysis variables are taken directly from the questionnaire and to that extent are self-explanatory. These include age, sex, household income, and highest educational qualification obtained. The analysis groups requiring further definition are set out below.

The Scottish Household Survey six-fold urban-rural classification

The six categories used in this classification are: 1) large urban, 2) other urban, 3) small accessible towns, 4) small remote towns, 5) accessible rural, 6) remote rural. For more details see Hope, S. et al (2000).

National Statistics Socio-Economic Classification ( NS- SEC)

The most commonly used classification of socio-economic status used on government surveys is the National Statistics Socio-Economic Classification ( NS- SEC). SSA respondents were classified according to their own occupation, rather than that of the 'head of household'. Each respondent was asked about their current or last job, so that all respondents, with the exception of those who had never worked, were classified. The seven NS- SEC categories are:

• Employers in large organisations, higher managerial and professional
• Lower professional and managerial; higher technical and supervisory
• Intermediate occupations
• Small employers and own account workers
• Lower supervisory and technical occupations
• Semi-routine occupations
• Routine occupations

The remaining respondents were grouped as "never had a job" or "not classifiable".

Scottish Index of Multiple Deprivation ( SIMD)

The Scottish Index of Multiple Deprivation ( SIMD) 2004 identifies the most deprived areas across Scotland. It is based on 31 indicators in the six individual domains of Current Income, Employment, Housing, Health, Education, Skills and Training and Geographic Access to Services and Telecommunications. SIMD 2004 is presented at data zone level, enabling small pockets of deprivation to be identified. The data zones are ranked from most deprived (1) to least deprived (6505) on the overall SIMD 2004 and on each of the individual domains. The result is a comprehensive picture of relative area deprivation across Scotland. ⁷

The SSA analysis used a variable created from SIMD data indicating the level of deprivation of the data zone in which the respondent lived. This allowed us to analyse differences between the attitudes and experiences of those living in the most and least deprived areas of Scotland.

Analysis techniques

Regression

For the more complex analysis in this report logistic regression models have been used to assess whether there is reliable evidence that particular variables are associated with each other.

Regression analysis aims to summarise the relationship between a 'dependent' variable and one or more 'independent' explanatory variables. It shows how well a respondent's score on the dependent variable can be estimated from knowledge of their scores on the independent variables. This technique takes into account relationships between the different independent variables (for example, between education and income, or social class and housing tenure). Regression is often undertaken to support a claim that the phenomena measured by the independent variables cause the phenomenon measured by the dependent variable. However, the causal ordering, if any, between the variables cannot be verified or falsified by the technique. Causality can only be inferred through special experimental designs or through assumptions made by the analyst. All regression analysis assumes that the relationship between the dependent and each of the independent variables takes a particular form. In logistic regression, the form of regression analysis used in this report, it is assumed that the relationship can be adequately summarised by an S-shaped curve, where the impact on the dependent variable of a one-point increase in an independent variable becomes progressively less the closer the value of the dependent variable approaches 0 or 1.

References

Bromley, C., Curtice, J., and Given,. L. (2005) Public Attitudes to Devolution: the First Four Years, London: The National Centre for Social Research..

Hope, S. et al (2000) Scotland's people: results from the 1999 Scottish Household Survey: Volume 1, Scottish Executive.

Park, A., Curtice, J., Thomson, K., Bromley, C. and Phillips, M., (2004), British Social Attitudes - the 21 ^st Report, London: Sage.

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