Survey on Early Learning and Child Care Arrangements (SELCCA)
Detailed information for 2018
Statistics Canada is gathering information from families who use child care as well as those who do not. The survey, which addresses child care in Canada for children younger than 6 years old, asks about the different types of early learning and child care arrangements that families use, difficulties some families may face when looking for care, as well as reasons for not using child care.
Data release - April 10, 2019
This survey is part of the Government of Canada's investment in early learning and child care. Information will be used to provide a current snapshot of the use of child care and of barriers to child care access. The results of this survey can be used to inform research, policies and programs aimed at improving the accessibility and affordability of high-quality early learning and child care in Canada.
- Child care
- Children and youth
Data sources and methodology
The target population is children across the 10 provinces and 3 territories of Canada who are less than 6 years old (as of February 28, 2019). Children living on reserves in the provinces are excluded from the target population.
The content for the Survey on Early Learning and Child Care Arrangements electronic questionnaire was drafted in consultation with several external subject matter experts.
The questionnaire underwent cognitive testing in the form of in-depth interviews in both of Canada's official languages, conducted by Statistics Canada's Questionnaire Design Resource Centre. The goal of the qualitative study was to test the survey content.
This is a sample survey.
This is a targeted respondent survey. The sampling unit is the person knowledgeable about the child care arrangements for a child who lives in their household and is less than 6 years of age.
The frame for the Survey on Early Learning and Child Care Arrangements was stratified by province and territory and a simple random sample was selected independently within each province and territory.
Sampling and sub-sampling:
Sufficient sample was allocated to each of the provinces and territories so that the survey could produce provincial level estimates, as well as estimates for the territories. An initial sample of 15,000 dwellings was selected and sent to collection.
Data collection for this reference period: 2019-01-15 to 2019-02-12
Responding to this survey is voluntary.
Data are collected directly from survey respondents either through an electronic questionnaire (EQ) or through CATI (computer assisted telephone interviewing).
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 eliminate potential duplicate records and to drop non-response and out-of-scope records.
In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.
After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file. Subsequent to this, invalid characters were deleted and the remaining data items were formatted appropriately.
This methodology type does not apply to this statistical program.
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 process of computing survey weights for each survey respondent involves several steps.
1) Each selected respondent is given an initial weight equal to the inverse of its selection probability from the sampling frame (CCB). Respondents identified as out-of-scope during collection are dropped from the sample.
2)The respondents weights are then adjusted to take into account non-response based on the province/territory, number of children and household income (estimated from CCB file).
3) The person (child) weights are obtained by multiplying each respondent's weight by the number of in-scope children in their household according to the CCB file.
Note that the person weights are not calibrated since there are no demographic counts for the population of parents and guardians of young children other than the ones from the frame (CCB).
Variance estimation is based on a re-sampling method called bootstrap estimation.
The Generalized Estimation System from Statistics Canada(G-Est) was used to generate the survey weights and bootstrap weights.
While rigorous quality assurance mechanisms are applied at all stages of the statistical process, the validation and detailed review of data by statisticians is the ultimate verification of quality prior to release. Many validation measures were implemented, they include:
a. Verification of estimates through cross-tabulations
b. Consultation with stakeholders internal to Statistics Canada
c. Consultation with external stakeholders
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 type does not apply to this statistical program.
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 (CI) or coefficient of variation (CV).
The following are approximate sampling error estimates for Canada level estimates. These are based on average results; these are not results for a specific variable.
- Approximate length of 95% confidence intervals for a proportion of 50% (Canada level): 4.0%
- Approximate length of 95% confidence intervals for a proportion of 10% (Canada level): 2.5%
- Approximate coefficients of variation (CVs) for a proportion of 10% (Canada level): 6%
The response rate for the Survey on Early Learning and Child Care Arrangements for the provinces was 52.7% and for the territories 41.1% with an overall response rate of 50.3%.
Non sampling error
The first type of errors treated were errors in questionnaire flow. For skips based on answered questions, all skipped questions were set to "Valid skip" (6, 96, 996, etc.). For skips based on "Non-response", all skipped questions were set to "Not stated" (9, 99, 999, etc.). The remaining empty items were filled with a numeric value (9, 99, 999, etc., depending on variable length). These codes are reserved for processing purposes and mean that the item was "Not stated".
The survey estimates are adjusted to account for non-response through the survey weights. To the extent that the non-responding persons differ from the rest of the sample, the results may be biased.
Coverage errors arise when there are differences between the target population and the observed population. The target respondent is the person knowledgeable (aged 15 years and older) about the child care arrangements for a child who lives in the household and is less than 6 years old. The survey frame is the Canada Child Benefit (CCB) file and it contains every parent who is registered to receive a benefit. It is estimated that the frame represents 96% of the children population of all ages. To the extent that the excluded population differs from the rest of the target population, the results may be biased.
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