Survey on Family Transitions (SFT)

Survey on Family Transitions (SFT)
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Detailed information for 2024

Status:

Active

Frequency:

Every 5 years

Record number:

4501

The General Social Statistics Program (GSSP) has two main objectives: a) to collect data on social trends in order to monitor changes in the living conditions and well-being of Canadians over time, and b) to provide updated information on specific social policy issues of current or emerging interest.

Data release - January 26, 2026

Description

The Survey on Family Transitions (SFT) explores the experiences of families in Canada through time by examining how individuals and families change during various stages of life - from childhood to adulthood to retirement.

Survey results will be used to develop programs and policies aimed at improving the well-being of children and families, such as parental leave, childcare services and pay equity. The results will also be used to help enhance and complement information on families from the census, and to compare families in Canada with those of other countries.

Statistical activity

This record originated in 1985 and is part of the General Social Survey Program (GSSP). GSSP data are integrated from administrative data, statistical modelling and alternative data collection approaches, in addition to a detailed survey on a given topic. The GSSP is comprised of surveys on core topics, using focus or exploratory questions and a standard set of socio-demographic questions used for classification. More recent surveys have also included some qualitative questions, which explore intentions and perceptions.

Subjects

  • Families, households and housing
  • Immigration and ethnocultural diversity

Data sources and methodology

Target population

The target population for the SFT is all persons aged between 20 and 79, living in private dwellings in the 10 provinces of Canada.
Excluded from the survey's coverage:
- residents of Yukon, the Northwest Territories, and Nunavut,
- full-time residents of institutions,
- residents of First Nations reserves.

Instrument design

The questionnaire was designed based on research and extensive consultations with key partners and data users. Qualitative testing of the survey questions, conducted by Statistics Canada's Questionnaire Design Resource Center (QDRC), was carried out, with respondents who were screened in based on representative criteria. Questions which worked well and others that needed clarification or redesign were highlighted. QDRC staff compiled a detailed report of the results along with their recommendations. All comments and feedback from qualitative testing were carefully considered and incorporated into the survey when possible. In addition, the EQ application underwent extensive qualitative testing by the Centre of Expertise in Accessibility (CEA). Recommendations from CEA were implemented into the final version of the application.

Sampling

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

The sample consists of a random sample of units selected from the 2021 Census of Population (short-form questionnaire) along with the Longitudinal Immigration Database (IMDB) and the permanent resident file received from Immigration, Refugees, Citizenship Canada (IRCC).

Sampling Unit:
This is a targeted respondent survey. The sampling unit is the person.

Stratification method:
Strata were defined to achieve sufficient sample sizes in each domain of estimation and optimize sample allocation. For non-immigrants and non-permanent residents, the frame for the SFT was stratified by province (Atlantic provinces regrouped). The landed immigrant population was instead stratified by classification of admission category (economic immigrants and other immigrants, immigrants sponsored by family, and refugees), and by admission period to Canada (less than 5 years ago, between 5 to 10 years ago, at least 10 years ago).

Sampling and sub-sampling:
Within each stratum, a sample was drawn using systematic sampling, after sorting the frame by dwelling identifier, to reduce the possibility of sampling more than one person per household.

Through a new program called the Disaggregated Data Action Plan (DDAP), Statistics Canada is producing detailed data to address gender gaps, racism and other systemic barriers, to apply fairness and inclusion to decisions that affect all people in Canada.

With DDAP funding, the SFT has increased its sample size of immigrants in order to produce more detailed disaggregated data on the immigrant population and to best represent this population.

The total sample size for the SFT is approximately 51,000 individuals.

Data sources

Data collection for this reference period: 2024-04-22 to 2024-09-20

Responding to this survey is voluntary.

Data were collected directly from survey respondents either through an electronic questionnaire (EQ) or through CATI (computer-assisted telephone interviewing). First contact is made by an introduction letter in the mail. Targeted respondents may have received e-mail invitations or a telephone call from a Statistics Canada interviewer to complete the survey. No proxy reporting is allowed. Respondents were interviewed in the official language of their choice. The average time to complete the survey is estimated at 30 minutes.

The information collected during the 2024 SFT was also linked with the IMDB for completed cases. The linkage falls under the omnibus record authority (Type B) as the linkage was used for data replacement.

Respondents were notified of the planned linkage before and during the survey. Any respondents who objected to the linkage of their data, had their objection recorded, and no linkage to their administrative data took place.

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

Error detection

The 2024 SFT used the Social Survey Processing Environment (SSPE), a set of generalized processing steps and utilities, to allow subject matter and survey support staff to specify and run the processing of the survey in a timely fashion with high quality outputs. The SSPE is a structured environment that monitors the processing of data, ensuring best practices and harmonized business processes are followed.

Edits were performed automatically and manually at various stages of processing at macro and micro levels. Data verification was carried out using consistency and flow edits. A series of checks were done to ensure the consistency of the survey data, for example, checking the respondent's reported age against the date of birth coming from the sample file. Flow edits were used to ensure respondents followed the correct path and fix off-path situations.

Most error detection was done through pre-determined edits programmed into the EQ system, which allows for a valid range of codes for each question and built-in edits, and automatically follows the flow of the questionnaire.

Head office performed the same checks as the EQ system as well as more specific validation of edits that are beyond the scope of automated flow and consistency edits. Records with missing or incorrect information were, in a small number of cases, completed, corrected deterministically, or imputed from information collected elsewhere in the questionnaire.

Imputation

In 2024, income questions were not asked in the survey. Income information was obtained by linking to the tax data of respondents who had agreed to the linkage. Personal income and family income data were obtained from T1 Family File (T1FF). Missing information for other respondents was imputed.

Estimation

When a probability sample is used, as is the case for the 2024 SFT, the principle behind estimation is that each person selected in the sample represents (in addition to himself or herself) several other persons not in the sample. For example, in a simple random sample of 2% of a population size of 1000, each person in the sample represents 50 persons in the population. The number of persons represented by a given person in the sample is usually known as the weight or weighting factor.

A weighting factor is made available to analysts on the microdata file:

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 20 to 79) having one or several given characteristics.

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

Estimates based on the survey data are also adjusted (by weighting) so that they are representative of the target population with regard to certain characteristics (age groups, gender, province). To the extent that the characteristics are correlated with those independent estimates, this adjustment can improve the precision of estimates.

Quality evaluation

While rigorous quality assurance mechanisms are applied across all steps of the statistical process, validation and scrutiny of the data by statisticians are the ultimate quality checks prior to dissemination. Many validation measures were implemented. They include:

1) analysis of changes over time,
2) verification of estimates through cross-tabulations, and
3) confrontation with other similar sources of data.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that 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.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

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. 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 the estimates produced based on the data from the 2024 SFT.

Response rate:

The overall response rate was 47.5%.

Non-sampling error:

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. Persons without good contact information 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.

Non-response could occur at several stages in this survey. Survey estimates are adjusted (i.e. weighted) to account for non-response cases. Other types of non-sampling errors can include response errors and processing errors.

Non-response bias:

The main method used to reduce non-response bias involved a series of adjustments to the survey weights to account for nonresponse as much as possible. Information was extracted from the frame and used to model and adjust for non-response.

Coverage error:

The SFT 2024 frame is based on a combination of the 2021 short-form Canadian Census of Population, the Longitudinal Immigration Database (IMDB) and the permanent resident file from IRCC (the latter two to ensure adequate coverage of recent immigrants). Coverage was improved (over coverage and under coverage may still exist) if we compare using several linked sources. All respondents in the ten provinces were interviewed by telephone or self-completed an electronic questionnaire. Survey estimates were adjusted (weighted) to represent all persons in the target population, including those not covered by the survey frame.

Other non-sampling errors:

For the 2024 SFT, significant effort was made to minimize bias by using a well-tested questionnaire, a proven methodology, specialized interviewers and strict quality control.

Documentation

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