Canadian Social Survey (CSS)
Detailed information for fourth quarter of 2022
The Canadian Social Survey (CSS) is Statistics Canada's recent data collection project. The goal is to understand social issues more rapidly by conducting surveys on different topics every three months.
Data release - February 13, 2023
The Canadian Social Survey (CSS) will collect information on a variety of social topics such as health, well-being, impacts of COVID-19, activities, time-use, emergency preparedness, quality of life, energy use, virtual health care and trust. The CSS will provide data at the national level (excluding the territories).
This information may be used by all levels of government and various organizations, to inform the delivery of services and supports for Canadians during and after the pandemic, and to guide policy development on a range of social and economic issues.
Data sources and methodology
The target population for the Canadian Social Survey is all non-institutionalized persons 15 years of age or older, living off-reserve in the 10 provinces of Canada.
The questionnaire was designed based on research and consultations with data users. Qualitative testing was carried out by Statistics Canada's Questionnaire Design Resource Centre (QDRC). 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.
This is a sample survey with a cross-sectional design.
The Canadian Social Survey sample is a stratified two-stage sample of one person from each dwelling in a sample.
At the first stage, the sampling unit is a dwelling. At the second stage, one person is selected within the dwelling.
Stratification is done by province and by expected number of household members aged 15 or older.
Sampling and sub-sampling
A stratified sample of 20,000 dwellings was selected probabilistically. Within a household, information is collected from one randomly selected household member aged 15 or older.
Data collection for this reference period: 2022-10-21 to 2022-12-04
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data are collected using self-response via an electronic questionnaire or by computer-assisted telephone interviewing. First contact is made either by an invitation letter in the mail, which provides a link and access code for completing survey electronically, or by telephone. A non-responding household may receive reminders by mail, by email or by SMS before they are contacted by a Statistics Canada interviewer to complete the questionnaire over the telephone. No proxy reporting is allowed. The respondents have the choice between French and English. Interviews are approximately 20 minutes.
View the Questionnaire(s) and reporting guide(s).
Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and remove duplicate records, records that were out-of-scope and records that did not meet minimum response criteria.
Imputation is a process used to determine and assign replacement values to resolve problems of missing, invalid or inconsistent data. This is done by changing some of the missing values and the responses on the record being edited to ensure that a plausible, internally consistent record is created. Imputation was performed on the socio-demographic variables that are included in the CSS.
The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is referred to as the survey weight. The steps for weighting, including an adjustment for out-of-scope records, a non-response adjustment and calibration, are described in chapter 7 of the CSS User Guide. These steps adjust the weights so that they align with the target population with regards to certain characteristics, such as age-sex groups by province and education levels. To the extent that these characteristics are correlated with the variables of interest, these adjustments can improve the accuracy of the survey estimates. Variance estimation is based on a resampling method called the bootstrap.
Statistics Canada's Generalized Estimation System was used to generate the survey weights and bootstrap weights.
While quality assurance mechanisms are applied at all stages of the statistical process, the validation and review of data by statisticians is the final verification of quality prior to release. Validation measures that were implemented include:
a) verification of estimates through cross-tabulations
b) consultation with stakeholders internal to Statistics Canada
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 microdata: 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 survey.
Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error can be expressed through a confidence interval or coefficient of variation.
The response rate for CSS-QLCL is estimated at 52.2%.
Measurement errors (sometimes referred to as response errors) occur when the response provided differs from the real value; such errors may be attributable to the respondent, the questionnaire, the collection method or the respondent's record-keeping system. Such errors may be random or they may result in a systematic bias if they are not random.
Processing errors are the errors associated with activities conducted once survey responses have been received. They include all data handling activities after collection and prior to estimation. Like all other errors, they can be random in nature, and inflate the variance of the survey's estimates, or they can be systematic, and introduce bias. It is difficult to obtain direct measures of processing errors and their impact on data quality especially since they are mixed in with other types of errors (nonresponse, measurement and coverage).
To mitigate potential nonresponse bias, the survey weights are adjusted for total non-response and are calibrated to population totals for age, sex, geography, and educational attainment.
Coverage errors consist of omissions, erroneous inclusions, duplications and misclassifications of units in the survey frame. Coverage errors may cause a bias in the estimates and the effect can vary for different sub-groups of the population.
The CSS data is collected from people aged 15 years and over living in private dwellings within the 10 provinces. Excluded from the survey's coverage are: residents of the Yukon, Northwest Territories, and Nunavut; full-time residents of institutions, and residents of reserves. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over.