Canadian Survey on the Provision of Child Care Services (CSPCCS)

Detailed information for April 2024

The purpose of this survey is to collect information on the provision of child care services in Canada for children ages 12 and under at the national, provincial and territorial level. Data was collected from licensed and unlicensed home-based and centre-based child care providers. Questions were asked about staff, services provided, enrollment and daily fees. The data will be used by Employment and Social Development Canada (ESDC) for policy research and development. Information may also be used by Statistics Canada for other statistical and research purposes.

Data release - March 19, 2025

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

Statistics Canada conducted the Canadian Survey on the Provision of Child Care Services (CSPCCS) in collaboration with Employment and Social Development Canada (ESDC). Data was gathered on:
- status and type of licensing of child care providers,
- type of child care services offered,
- maximum capacity,
- number of enrolled children by age group,
- daily fees,
- type of building where child care services are provided,
- number, type of employment, and educational training of child care employees, and
- sources of operating funds.

Results were produced at the national, provincial and territorial level on child care provision by centres and licensed and unlicensed homes.

Subjects

• Child care
• Children and youth

Data sources and methodology

Target population

The target population for this survey includes all child care locations in Canada with an annual revenue of at least $2,500 per year. To identify these units, the sampling frame was built by taking locations coded to North American Industry Classification System (NAICS) 624410 (Child day-care services) on the Business Register in addition to providers matched from licensed provincial and territorial lists, whose primary activity may not fall under NAICS 624410. All units with revenue less than $2,500 were excluded from the frame.

Instrument design

The questionnaire was developed by Statistics Canada in partnership with Employment and Social Development Canada (ESDC). Statistics Canada conducted cognitive testing with selected respondents and made recommendations that were implemented to finalize the questionnaire. Data were collected electronically.

Sampling

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

The sampling frame is extracted from Statistics Canada's Business Register (BR). The sampling unit is the location, as defined in the Business Register.

Sampling unit
The sampling units are all home-based licensed, home-based unlicensed and centre-based child care locations in Canada.

Stratification method
Units were stratified into three groups: Centres, Licensed Homes and Unlicensed Homes. These three strata were further stratified into eleven regions, consisting of the ten provinces and the territories combined into one region.

Centres on the frame that were identified as having a particularly large number of employees on the Business Register formed their own stratum where all locations within it were selected in the sample with certainty.

Sampling and sub-sampling
The total sample size was set at 20,000 units, and units were allocated to ensure similar quality across regions and balance among the estimation domains. The total sample is allocated at the strata level in order to meet the required precision when estimating proportions for the three types of services at the provincial level.

Data sources

Data collection for this reference period: 2024-04-02 to 2024-06-28

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data was collected via electronic questionnaire (EQ).

Respondents with an email address in the Business Register received an email invitation while the remainder received an invitation letter in the mail with a Secure Access Code to access the EQ.

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

Error detection

Error detection is an integral part of data processing activities. Prior to imputation, a series of edits are applied to the collected data to identify errors and inconsistencies. Errors and inconsistencies in the data are reviewed and resolved by referring to data for similar units in the survey and information from external sources. If a record cannot be resolved, it is flagged for imputation. Finally, edit rules are incorporated into the imputation system to detect and resolve any remaining errors, as well as to ensure that the imputed data are consistent.

Imputation

After microdata verification, a variable was created for each of the survey variables to identify those that had either failed the verification rules or had missing values. Imputation was performed to reduce the amount of missing, inconsistent or incomplete data. The missing data were usually imputed using a randomly selected donor inside the imputation class. These imputation classes were formed based on statistical analysis performed with frame information or previous variables on the questionnaire. In some situations, the data were imputed using historical responses from the same business, or imputed from information contained on an auxiliary file.

For donor imputation, a minimum number of units was required within each imputation class. When imputation classes were too small, larger classes were created by combining several classes together.

Estimation

Estimation is a process by which Statistics Canada obtains values for the population of interest so that it can draw conclusions about that population based on information gathered from only a sample of the population. For this survey, the sample used for estimation comes from a single-phase sampling process.

An initial sampling weight (the design weight) is calculated for each unit of the survey and is simply the inverse of the probability of selection. The weight calculated for each sampling unit indicates how many other units it represents.

However, since some of the selected units did not answer the survey, reweighting is performed on the responding units so that their final weights still represent the whole target population. The response mechanism can be considered as a second-phase of the sampling process.

After the reweighting is performed, a calibration process is performed so that the weighted totals per calibration groups equal the population totals.

Estimation of proportions is done using the calibrated weights to calculate the population totals in the domains of interest.

Quality evaluation

Estimates were reviewed to ensure that the findings are logical and quality checks were carried out to ensure that estimates are consistent. Atypical results were flagged for investigation and were corrected as necessary.

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 statistical program.

Data accuracy

There are two types of errors which can impact the data: sampling errors and non-sampling errors.

Estimates are subject to sampling error. This error is expressed either as a standard error (SE) or a coefficient of variation (CV). The following rules based on the standard error (SE) are used to assign a measure of quality to all of the estimates of percentages (expressed as a percentage):
A = Excellent (0.00% to less than 2.50%)
B = Very good (2.50% to less than 5.00%)
C = Good (5.00% to less than 7.50%)
D = Acceptable (7.50% to less than 10.00%)
E = Use with caution (10.00% to less than 15.00%)
F = Too unreliable to be published (Greater than or equal to 15%, data are suppressed)

The following rules based on the coefficient of variation (CV) are used to assign a measure of quality to all of the estimates of counts and totals:
A = Excellent (0.00% to less than or equal to 5.00%)
B = Very good (5.01% to less than or equal to 10.00%)
C = Good (10.01% to less than or equal to 15.00%)
D = Acceptable (15.01% to less than or equal to 25.00%)
E = Use with caution (25.01% to less than or equal to 35.00%)
F = Too unreliable to be published (Greater than 35.00%, data are suppressed)

Non-sampling errors may occur for various reasons during the collection and processing of the data. For example, non-response is an important source of non-sampling error. Under or over-coverage of the population, differences in the interpretations of questions and mistakes in recording and processing data are other examples of non-sampling errors. To the maximum extent possible, these errors are minimized through careful design of the survey questionnaire and verification of the survey data.