ANNEX B -Technical Details of the Survey
The Scottish Social Attitudes series
1. The Scottish Social Attitudes (SSA) survey was launched by ScotCen Social Research in 1999, following the advent of devolution. Based on annual rounds of interviews of between 1,200 to 1,500 people drawn using probability sampling (based on a stratified, clustered sample), it aims 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 ScotCen's parent organisation, NatCen Social Research 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, 2012 for more details of the BSA survey).
2. SSA has been conducted annually each year since 1999, with the exception of 2008. The survey has a modular structure. In any one year it typically contains three to 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 individual modules each year. These bodies have included the Economic and Social Research Council, the Scottish Government and various charitable and grant awarding bodies, such as the Nuffield Foundation and Leverhulme Trust. 2011 funders were the Scottish Government, the Leverhulme Trust and the Nuffield Foundation.
3. Where this report discusses differences between two percentages (either across time, or between two different groups of people within a single year), this difference is significant at the 95% level or above, unless otherwise stated. Differences between two years were tested using standard z-tests, taking account of complex standard errors arising from the sample design. Differences between groups within a given year were tested using logistic regression analysis, which shows the factors and categories that are significantly (and independently) related to the dependent variable (see below for further detail). This analysis was done in PASW 18, using the CS logistic function to take account of the sample design in calculations.
The 2011 survey
4. The 2011 survey contained modules of questions on:
- Government and public services in Scotland (funded by the Scottish Government Office of the Chief Researcher from 2004-2007 and again in 2009 - 2011)
- Constitutional change (funded by the Nuffield Foundation)
- National identity and the 2011 Scottish Elections (funded by the Leverhulme Trust and undertaken in collaboration with Frank Bechhofer and David McCrone at the University of Edinburgh).
5. In addition, it included a small number of questions on the Scottish Election, funded by the University of Manchester. Separate programmes of dissemination are planned for each of the other modules. This technical annex covers the methodological details of the survey as well as further discussion of the analysis techniques used in this report.
6. The survey is designed to yield a representative sample of adults aged 18 or over, living in Scotland. The sample frame is the Postcode Address File (PAF), a list of postal delivery points compiled by the Post Office. The detailed procedure for selecting the 2011 sample was as follows:
I. 81 postcode sectors were selected from a list of all postal sectors in Scotland, with probability proportional to the number of addresses in each sector for addresses in urban areas and a probability of twice the address count for sectors in rural areas (i.e. the last 3 categories in the Scottish Government's 6 fold urban-rural classification). Prior to selection the sectors were stratified by Scottish Government urban-rural classification, region and percentage of household heads recorded as being in non-manual occupations (SEG 1-6 and 13, taken from the 2001 Census).
II. 30 addresses were selected at random from each of these 81 postcode sectors
III. Interviewers called at each selected address and identified its eligibility for the survey. Where more than one dwelling unit was present at an address, all dwelling units were listed systematically and one was selected at random using a computer generated random selection table. In all eligible dwelling units with more than one adult aged 18 or over, interviewers had to carry out a random selection of one adult using a similar procedure.
7. The Scottish Social Attitudes survey involves a face-to-face interview with respondents and a self-completion section (completed using Computer Assisted Personal Interviewing in 2011). The numbers completing each stage in 2011 are shown in Table 1. See Bromley, Curtice and Given (2005) for technical details of the 1999-2004 surveys, Given and Ormston (2006) for details of the 2005 survey, Cleghorn, Ormston and Sharp (2007) for the 2006 survey, Ormston (2008) for the 2007 survey, Ormston (2010) for the 2009 survey and Ormston and Reid (2011) for the 2010 survey.
|Vacant, derelict and other out of scope 1||266||10.9|
|Achievable or 'in scope'||2164|
|Unknown eligibility 2||30||1.2|
|Interview not achieved|
|Other non-response 5||140||5.8|
Notes to table
1 This includes empty / derelict addresses, holiday homes, businesses and institutions, and addresses that had been demolished.
2 'Unknown eligibility' includes cases where the address could not be located, where it could not be determined if an address was residential and where it could not be determined if an address was occupied or not.
3 Refusals 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.
4 Non-contacts comprise households where no one was contacted after at least 6 calls and those where the selected person could not be contacted.
5 'Other non-response' includes people who were ill at home or in hospital during the survey period, people who were physically or mentally unable to participate and people with insufficient English to participate.
Sample size for previous years
8. The table below shows the achieved sample size for the full SSA sample (all respondents) for all previous years.
|Survey year||Achieved sample size|
9. All percentages cited in this report are based on weighted data. The weights applied to the SSA 2011 data are intended to correct for three potential sources of bias in the sample:
- Differential selection probabilities
- Deliberate over-sampling of rural areas
10. Data were weighted to take account of the fact that not all households or individuals have 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. Differences between responding and non-responding households were taken into account using information from the census about the area of the address as well as interviewer observations about participating and non-participating addresses. Finally, the weights were adjusted to ensure that the weighted data matched the age-sex profile of the Scottish population (based on 2010 mid-year estimates from the General Register Office for Scotland).
11. Fieldwork for the 2011 survey ran between early June and September 2011, with 80% of interviews completed by the end of July and 96% by the end of August. An advance letter was sent to all addresses and was followed up by a personal visit from a ScotCen interviewer. Interviewers were required to make a minimum of 6 calls at different times of the day (including at least one evening and one weekend call) in order to try and contact respondents. All interviewers attended a one day briefing conference prior to starting work on the study.
12. 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. Table 1 (above) summarises the response rate and the numbers completing the self-completion section in 2011.
13. Most of the analysis variables are taken directly from the questionnaire and are self-explanatory. These include age, sex, household income, and highest educational qualification obtained.
14. Where this report discusses differences between two percentages (either across time, or between two different groups of people within a single year), this difference is significant at the 95% level or above, unless otherwise stated. Differences between two years were tested using standard z-tests, taking account of complex standard errors arising from the sample design. Differences between groups within a given year were tested using logistic regression analysis, which shows the factors and categories that are significantly (and independently) related to the dependent variable (see below for further detail). This analysis was done in PASW 18, using the CS logistic function to take account of the sample design in calculations.
15. Regression analysis aims to summarise the relationship between a 'dependent' variable and one or more 'independent' explanatory variables. It shows how well we can estimate a respondent's score on the dependent variable 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.
16. All regression analysis assumes that the relationship between the dependent and each of the independent variables takes a particular form. This report was informed by logistic regression analysis - a method that summarises the relationship between a binary 'dependent' variable (one that takes the values '0' or '1') and one or more 'independent' explanatory variables. The tables in this annex show how the odds ratios for each category in significant explanatory variables compares to the odds ratio for the reference category (always taken to be 1.00).
17. Taking Model 1 (below), the dependent variable is thinking the Scottish Government has most influence over how Scotland is run. If the respondent said the Scottish Government did have most influence, the dependent variable takes a value of 1. If not, it takes a value of 0. An odds ratio of above 1 means that, compared with respondents in the reference category, respondents in that category have higher odds of saying the Scottish Government has most influence. Conversely, an odds ratio of below 1 means they have lower odds of saying this than respondents in the reference category. The 95% confidence intervals for these odds ratios are also important. Where the confidence interval does not include 1, this category is significantly different from the reference category. If we look at party identification in Model 1, we can see that those who do not identify with any political party have an odds ratio of 0.21, indicating that they have lower odds compared with SNP identifiers (who were the reference category) of saying standards the Scottish Government has most influence. The 95% confidence interval (0.10 - 0.43) does not include 1, indicating this difference is significant.
18. The significance of each independent variable is indicated by 'P'. A p-value of 0.05 or less indicates that there is less than a 5% chance we would have found these differences between the categories just by chance if in fact no such difference exists, while a p-value of 0.01 or less indicates that there is a less than 1% chance. P-values of 0.05 or less are generally considered to indicate that the difference is highly statistically significant, while a p-value of 0.06 to 0.10 may be considered marginally significant.
19. Regression analyses were conducted using the Complex Survey command (CS Logistic) in PASW 18. CS Logistic models can account for complex sample designs (in particular, the effects of clustering and associated weighting) when calculating odds ratios and determining significance. The table below includes only those variables found to be significant after the regression models were run using CS logistic.
| Dependent variable encoding
1 = Scottish Government
0 = NOT Scottish Government
|Odds ratio||95% confidence interval|
|Party identification (p = 0.001)|
|Other/Don't Know/Refused/Not applicable||0.41||0.22-0.76|
|Affect of Scottish Parliament on voice in UK (p = 0.000)|
|Makes no difference||0.37||0.25-0.55|
Nagelkerke R2 = 19.3%
Other factors included in model but which were not significant after other factors were accounted for were: who should make decisions about Scotland, who is responsible for changes in economy, who is responsible for changes in standard of living, who is responsible for standards in health service, education and public transport.
References in technical annex
Bromley, C., Curtice, J., and Given, L. (2005) Public Attitudes to Devolution: the First Four Years, London: The National Centre for Social Research.
Given, L and Ormston (2006) Scottish Social Attitudes survey 2005: Scottish Executive Core module - technical report, Scottish Executive Social Research.
Cleghorn, N, Ormston, R & Sharp, C (2007) Scottish Social Attitudes survey 2006: Core module technical report, Scottish Executive Social Research.
Ormston, R (2008) Scottish Social Attitudes survey 2007 Core module: Report 1 - Attitudes to government in Scotland, Scottish Government Social Research.
Ormston, R (2010) Scottish Social Attitude survey 2009: Core Module - Attitudes to government, the economy and public services, Scottish Government Social Research.
Park, A, Clery, E, Curtice, J, Phillips, M and Utting, D (2012) British Social Attitudes 28, London: Sage
Email: Linzie Liddell
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