General Social Survey - Family, Social Support and Retirement (GSS)

Detailed information for 2007 (Cycle 21)

Status:

Active

Frequency:

Every 5 years

Record number:

4502

The two primary objectives of the General Social Survey (GSS) are: to gather data on social trends in order to monitor changes in the living conditions and well being of Canadians over time; and to provide information on specific social policy issues of current or emerging interest.

This survey collects data on family, social support and retirement for Canadians aged 45 years and over. The purpose of this survey is to better understand the needs and experiences of these Canadians by examining key transitions related to their families, care giving and receiving, work and retirement.

Data release - September 8, 2008

Description

This survey collects data on family, social support and retirement for Canadians aged 45 years and over. The purpose of this survey is to better understand the needs and experiences of these Canadians by examining key transitions related to their families, care giving and receiving, work and retirement.

The survey collects information on topics such as well-being, family composition, retirement decisions and plans, care giving and care receiving experiences, social networks and housing. Collecting similar data over time allows us to examine the changes that have occurred in specific areas in the lives of Canadians.

Results from this survey will have an impact in the areas of health, income security, employment and lifelong learning, marriage and family, housing, care-receiving and care-giving and retirement.

Statistical activity

This record is part of the General Social Survey (GSS) program. The GSS, originating in 1985, conducts telephone surveys. Each survey contains a core topic, focus or exploratory questions and a standard set of socio-demographic questions used for classification. More recent cycles have also included some qualitative questions, which explore opinions and perceptions.

Until 1998, the target sample of respondents was approximately 10,000 persons. This was increased in 1999 to 25,000. With a sample of respondents of 25,000, results are available at both the national and provincial levels and possibly for some special population groups such as disabled persons and seniors.

Subjects

  • Care and social support
  • Health and disability among seniors
  • Housing and living arrangements
  • Seniors
  • Work and retirement

Data sources and methodology

Target population

The target population is non-institutionalized persons 45 years of age or older, living in the ten provinces.

In the GSS, all respondents were contacted and interviewed by telephone. Thus persons in households without telephones cannot be interviewed. However, persons living in such households represent less than 2% of the target population. Interviews are not conducted by cellular telephone so persons with only cellular telephone service are also excluded; again, this group makes up a very small proportion of the population, less than 5%. (Survey of Household Spending - December 2005).

Instrument design

The questionnaire was designed based on qualitative testing (focus groups), a pilot test and interviewer debriefing.

Sampling

This is a sample survey with a cross-sectional design.

The sample for GSS-21 had two components:

1. Among respondents to the GSS-20 (from 2006), those who were aged 45 and above during GSS-21 collection were identified and included in the sample.
2. The remaining portion of the sample was selected through a technique called "Random Digit Dialling" (RDD) which randomly generates a list of phone numbers that is used to reach households. A survey respondent is then selected once contact is made with the household.
Note that respondents to GSS-20 were originally selected using RDD techniques.

In order to carry out sampling, each of the ten provinces was divided into strata. Many of the Census Metropolitan Areas (CMAs) were considered separate strata: St-John's, Halifax, Montreal, Quebec, Toronto, Ottawa, Hamilton, Winnipeg, Regina, Saskatoon, Calgary, Edmonton, Vancouver and Victoria. The CMAs not on this list are located in Quebec and Ontario. Two more strata were formed by grouping the remaining CMAs in each of these two provinces. Finally, the non-CMA areas of each of the ten provinces were also grouped to form their own strata. The sample was allocated to each of these 27 strata.

The sample was evenly distributed over the 10 months to represent seasonal variation in the information.

Data sources

Data collection for this reference period: 2007-03-05 to 2007-12-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data collection is conducted by Computer Assisted Telephone Interviewing (CATI) methods.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Error detection was done through edits programmed into the CATI system.

The CATI data capture program allowed a valid range of codes for each question and built-in edits, and automatically followed the flow of the questionnaire.

All survey records were subjected to computer edits throughout the course of the interview. The CATI system principally edited the flow of the questionnaire and identified out of range values. As a result, such problems could be immediately resolved with the respondent. If the interviewer was unable to correctly resolve the detected errors, it was possible for the interviewer to bypass the edit and forward the data to head office for resolution. All interviewer comments were reviewed and taken into account in head office editing.

Head office edits performed the same checks as the CATI system as well as more detailed edits.

Imputation

The flow editing carried out by head office followed a 'top down' strategy, in that whether or not a given question was considered "on path" was based on the response codes to the previous questions. If the response codes to the previous questions indicated that the current question was "on path", the responses, if any, to the current question were retained, though "don't know" was recoded as 9 (99 or 999, etc.) and refusals were recoded as "Not Stated", i.e. 8 (98 or 998, etc.). If the response codes to the previous questions indicated that the current question was "off path" because the respondent was clearly identified as belonging to a sub-population for which the current question was inappropriate or not of interest, the current question was coded as "Not Asked", i.e. 7 (97 or 997, etc.).

Due to the nature of the survey, imputation was not appropriate for most items so missing data were coded as 'Not stated'.

However, non-response was not permitted for those items required for weighting. Values were imputed in the rare cases where either of the following was missing: sex or number of residential telephones.

Estimation

When a probability sample is used, as was the case for the GSS, the principle behind estimation is that each person selected in the sample represents (in addition to himself/herself) several other persons not in the sample. For example, in a simple random sample of 2% of the population, each person in the sample represents 50 persons in the population (himself/herself and 49 others). The number of persons represented by a given respondent is usually known as the weight or weighting factor.

GSS Cycle 21 was a survey of individuals and the analytic files contain questionnaire responses and associated information from 23,404 respondents.

Two weighting factors were placed on the Main File. They are listed and explained below:

WGHT_PER: This is the basic weighting factor for analysis at the person level, i.e. to calculate estimates of the number of persons (non-institutionalized and aged 45 or over) having one or several given characteristics.

WGHT_HSD: This is the usual GSS household weight, to be used only for estimate of household characteristics. For example, to estimate the number of households that live in low-rise apartments, WGHT_HSD should be summed over all records with this characteristic.

In addition to the estimation weights, bootstrap weights have been created for the purpose of design-based variance estimation.

Quality evaluation

Quality assurance measures were implemented at every collection and processing step. Measures included recruitment of qualified interviewers, training provided to interviewers for specific survey concepts and procedures, observations of interviews to correct questionnaire design problems and instruction misinterpretations, procedures to ensure that data capture errors were minimized and edit quality checks to verify the processing logic. Data are verified to ensure internal consistency and they are also compared to other published sources.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

For micro data: content is reduced and modified. For tabular data: sensitive cells correction methods such as cell collapsing and suppression are applied.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

The methodology of this survey has been designed to limit the number of errors and to reduce their potential effects. However, the results of the survey remain subject to both sampling and non-sampling error.

Sampling error:
As the data are based on a sample of persons they are subject to sampling error. That is, estimates based on a sample will vary from sample to sample, and typically they will be different from the results that would have been obtained from a complete census. The potential range of this difference has been estimated for key data and used to produce tables that can be used to estimate the sampling variability of many estimates. More precise estimates of the sampling variability of estimates can be produced with the bootstrap method using bootstrap weights that have been created for this survey. The bootstrap method was used to estimate the sampling variability for all of the estimates produced based on the data from GSS Cycle 21. Estimates with high sampling variability are indicated in this publication and all of the highlighted differences between subgroups of the population are significant at the 95% level.

Non-sampling error:
Even a census of the population of interest produces estimates subject to error. While these are called non-sampling errors, estimates from samples still contain errors of this type. Common sources of these errors are imperfect coverage and non-response.

Coverage errors (or imperfect coverage) arise when there are differences between the target population and the surveyed population. Households without telephones represent a part of the target population that was excluded from the surveyed population. To the extent that the excluded population differs from the rest of the target population, the results may be biased. In general, since these exclusions are small, one would expect the biases introduced to be small.

The overall response rate for GSS cycle 21 based on the two components of the sample was close to 58%. Non-response could occur at several stages in this survey. There were two stages of information collection: at the household level and at the individual level. Some non-response occurred at the household level, and some at the individual level. Survey estimates have been adjusted (i.e. weighted) to account for non-response cases. To the extent that the non-responding households and persons differ from the rest of the sample, the results may be biased.

Other types of non-sampling errors can include response errors and processing errors.

Documentation

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