National Cannabis Survey

Detailed information for 2023





Record number:


The main objective of the National Cannabis Survey is to obtain detailed information about the habits of people who use cannabis, including cannabis purchasing and usage behaviours. The survey aims to understand how many Canadians use and do not use cannabis. Health Canada and other organizations will use the data to monitor changes in cannabis use.

Data release - March 18, 2024


The survey will be used to understand cannabis use and purchasing patterns in Canada since the legalization of cannabis, its impact on the Canadian economy, and to inform evidence-based national and provincial strategies, policies, and programs.

Reference period: The reference period in the questionnaire is the previous three months.


  • Economic accounts
  • Health

Data sources and methodology

Target population

The target population for the survey is non-institutionalized persons 18 years of age or older living in Canada's ten provinces, who are not members of collectives or living on reserves.

Instrument design

The original content for the National Cannabis Survey electronic questionnaire was drafted in consultation with the System of National Accounts team within Statistics Canada as well as several other federal government departments and agencies, including the survey sponsor, Health Canada, the Public Health Agency of Canada, Public Safety Canada and the Department of Justice of Canada.

The questionnaire was subject to 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 with a cross-sectional design.

Two different sampling frames were used for the survey. Youths aged 18 to 24 are covered through a person-level frame, while persons aged 25 and over are covered through a dwelling frame.

Stratification method:
The person-based frame was stratified by province, and a sample random sample of youths was selected independently within each province. Similarly, the dwelling frame was stratified by province, and a simple random sample of dwellings was selected within each province.

Sampling and sub-sampling:
A sample of 6,200 youths aged 18 to 24 was selected from the person-level frame and sent to collection. As well, a sample of 12,000 dwellings was selected from the dwelling frame; during collection, a person aged 25 and over was randomly selected from each sampled dwelling to participate in the survey.

Sampling unit:
The ultimate unit of analysis for both samples is the person.

Data sources

Data collection for this reference period: 2023-07-14 to 2023-10-15

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data are collected either through an electronic questionnaire or through computer assisted telephone interviewing.

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

Error detection

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.

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. Lastly, 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 dwelling is given an initial weight equal to the inverse of its selection probability from the sampling frame. Dwellings identified as out-of-scope during collection are dropped from the sample.

2) The weights for responding households are adjusted to represent the households that did not respond. Adjustment factors are calculated separately, by province, using a non-response model based on frame information.

3) The household weights are calibrated so that the sum of the weights match province level household size demographic counts.

4) Person weights are computed by multiplying the household level weights by the inverse of the probability of selecting the person within the household.

5) Each individual selected from the person frame is given an initial weight equal to the inverse of the selection probability from the sampling frame. Individuals identified as out of scope are dropped from the sample.

6) The respondent weights are adjusted to represent the individuals who did not respond to the survey. Adjustment factors are computed separately by province based on a non-response model using frame information.

7) The person weights coming from the household sample and the person sample are pooled together.

8) The person weights are calibrated so that the sum of the weights match demographic population counts at the region level by age group and by gender. The weights are also calibrated to demographic counts for large Census Metropolitan Areas.

Quality evaluation

While quality assurance mechanisms are applied at all stages of the statistical process, validation and detailed data review by statisticians are the final quality verifications prior to release. Many validation measures are implemented, including:

a. verification of estimates through cross-tabulation

b. consultation with stakeholders internal to Statistics Canada

c. consultation with external stakeholders.

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 type does not apply to this statistical program.

Data accuracy

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.

Non-sampling error

Non-sampling errors can be defined as errors arising during the course of virtually all survey activities, apart from sampling. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors, and other types of processing errors.

Non-response bias

The survey estimates are adjusted to account for non-response through the survey weights. To the extent that the non-responding households and persons differ from the rest of the sample, the results may be biased. The response rate for the survey was 44%.

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