Canadian Internet Use Survey (CIUS)

Detailed information for 2009

Status:

Active

Frequency:

Every 2 years

Record number:

4432

The Canadian Internet Use Survey (CIUS) measures the extent and scope to which individual Canadians use the Internet.

Data release - May 10, 2010 (excluding electronic commerce); September 27, 2010 (Electronic commerce: Internet Shopping)

Description

The Canadian Internet Use Survey (CIUS) measures the extent and scope to which individual Canadians use the Internet. Survey content includes the location of use (e.g., at home, at work), the frequency and intensity of use, the specific uses of the Internet from the home, the purchase of products and services (electronic commerce), and other issues related to Internet use (such as concerns over privacy). This content is supplemented by information on individual and household characteristics (e.g., age, income, education, family type) and some geographic detail (e.g. province, urban/rural, and Census Metropolitan Area).

The Canadian Internet Use Survey results are widely disseminated to a variety of users. All levels of government can use CIUS to shape policies and programmes related to the Internet (i.e. uptake and barriers, high speed access, Government on-line and other communication initiatives) and electronic commerce. Also, the Organization for Economic Cooperation and Development (OECD) uses the results for international benchmarking and comparison studies.

The CIUS data support a wide range of research initiatives. In academia, micro data are made available to students and researchers within universities and colleges under the Data Liberation Initiative. The survey results are also used in the private sector for market research, as well as for consultation on regulatory issues related to the internet. Finally, the results of the CIUS are widely quoted in the media reflecting a high level of interest in the Internet and its users.

The CIUS replaces the Household Internet Use Survey (HIUS, see Summary of changes over time), conducted from 1997 to 2003, which focused on household Internet penetration. The new survey was redesigned to focus more on Internet use by individuals and to conform to international standards regarding Internet statistics. Because CIUS collects information from the individual and HIUS was based on the household, it is not appropriate to directly compare results from these two surveys.

Reference period: 12 months prior to collection date

Collection period: Month following reference period

Subjects

  • Individual and household internet use
  • Information and communications technology

Data sources and methodology

Target population

The target population is residents of Canada 16 years of age or older excluding: Residents of the Yukon, Northwest Territories and Nunavut, Inmates of Institutions, Persons living on Indian Reserves, and Full time members of the Canadian Forces.

Instrument design

The survey design is based on the OECD's model survey adapted for Canadian needs. The questionnaire was designed by Statistics Canada in consultation with stakeholders and in consideration of the data needs of the larger research and policy communities.

Testing of the 2005 questionnaire instrument was done in two phases by Statistics Canada's Questionnaire Design Research Centre (QDRC) using focus group methodology in the latter part of 2003. For 2007, content was modified to reflect feedback from respondents as well as interviewers from 2005 and to reflect changing Internet uses and activities as identified by an inter-departmental working group. In addition, some modules asked in 2005 were not repeated for 2007.

For 2009, there were minimal content and design changes. Questions which asked the respondent if they used the Internet to search for health or medical or government information and /or communicate with governments in Canada were dropped. Only one question related to government online was preserved.

The questionnaire was designed to follow standard practices and wording, when applicable, in a computer-assisted interviewing environment. This included the automatic control of question wording and flows that depended upon answers to earlier questions and the use of on-line edits to check for logical inconsistencies and gross capture errors. The computer application for data collection was subjected to extensive modular and end-to-end testing before its use in the survey.

Sampling

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

The CIUS was administered to a sub-sample of the individuals already selected for the Labour Force Survey (LFS), record number 3701. The LFS uses a stratified, multi-stage cluster design employing probability sampling at all stages to select a representative sample of households from Canada's ten provinces, excluding persons living on Indian Reserves, full-time members of the Canadian Forces and inmates of institutions. Every month, one-sixth of the LFS sample is replaced by a new "birth" panel of dwellings.

The 2009 CIUS sample begins with the households in four of the five non-birth panels from the November LFS. When contact is made with the households selected by the CIUS, the computer survey application randomly selects one eligible member, 16 years of age or older. The final sample size was of 23,178 individuals.

Data sources

Data collection for this reference period: 2009-11-15 to 2009-12-06

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

In almost all cases, the LFS interview will have been completed by a responsible member of the household before the CIUS interview will begin. This individual generally provides the LFS responses for all household members. In any given month's collection, about 65% of the information collected for the LFS can be proxy responses, provided on behalf of another household member.

Following the LFS interview, the interviewer will ask to speak to the individual selected for the CIUS. Depending on this person's availability and operational constraints, some of the CIUS interviews were attempted at the same time as the corresponding LFS interview. Because the CIUS is a non-proxy survey, only the person randomly selected for the CIUS can answer the questionnaire. Interviewers routinely ask for and record the best time to call back in order to complete the interview, and the automated call scheduler manages follow-up calls in order to try different times of day throughout the collection period.

Interviews were conducted from Statistics Canada's regional offices using a Computer Assisted Telephone Interviewing (CATI) application. No Computer Assisted Personal Interviewing (CAPI) was conducted in 2009 to reduce collection costs. CAPI nonresponse was treated by adjusting the weights using reported LFS characteristics (see Estimation).

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

Error detection

The CIUS questionnaire incorporates many features to maximise the quality of the data collected. There are multiple edits in the computer assisted interview questionnaire to compare the entered data against unusual values for incomes and for on-line expenditures. Other edits check for logical inconsistencies in these sections of the questionnaire (e.g., personal income greater than household income) as well as in other sections with multiple choice responses. When an edit fails, the interviewer is prompted to correct the information (with the help of the respondent). For most of the income and expenditure edit failures, the interviewer has the ability to override the edit failure if it cannot be resolved. As well, the interviewer has the ability to enter a response of Don't Know or Refused if the respondent does not answer the question.

Once the data are received back at head office an extensive series of processing steps is undertaken to examine each record received. A top-down flow edit cleaned up any paths that may have been mistakenly followed during the interview. The editing and imputation phases of processing identify logically inconsistent or missing information items, and correct such errors related to incomes and on-line expenditures (for example, the amount spent on goods and services from companies in Canada is greater than the total amount spent on-line).

In an additional step, suspiciously large reported values for personal or household incomes and the number of Internet orders or their value are identified as "outliers". These few records were treated by replacing the suspicious values by ones from respondents with similar demographic characteristics in the imputation step of processing.

Imputation

Imputation is the process that supplies valid values for those variables that have been identified as either invalid or missing from a respondent's record on the data file. The new values are supplied in such a way as to preserve the underlying structure of the data and to ensure that the resulting records will pass all required edits. Imputation was limited in the CIUS to item non-response for household and personal incomes and for the number of orders and their value for e-commerce spending (from Canadian companies and in total). Imputation was done by the Impudon software using a nearest-neighbour method which searches for "donor" records from individuals with complete and consistent values. The recipient records are imputed by a donor chosen from a group of records with similar demographic characteristics. In the case of income, LFS data on the usual weekly earnings for a recipient and the household (when available) were used to select the donor with the most similar values.

In total, 13,900 respondents (60%) were eligible donors having reported both household and personal incomes. Respondents who did not provide a dollar estimate of their incomes were asked a series of questions in order to derive an income range. Almost 2,700 respondents (11.5%) did not provide any information on their incomes. The reported income ranges and the missing income information were imputed by the donor values in a series of steps, depending on the information available for other variables involved in forming the imputation groups.

For the number of online orders and their value, donor imputation was also used. Again, the donor records were chosen from a group of records with similar demographic characteristics, as well as, similar Internet shopping behaviour (e.g. types of goods and services). Moreover, the relative imputation rate serves as a data quality indicator. The rates for 2009, based on value-weighted estimates are the following. For every 100 online orders estimated from the survey, less than 5 orders were imputed. Similarly with the value of orders, for every $100 in online orders estimated from the survey, only $6.40 was imputed.

Estimation

Estimates are produced using weights attached to each sampled unit, or individual. The weight of a sampled individual indicates the number of people in the population that the unit represents. The initial weight was provided by the LFS and incorporated the probability of selecting the individual in their sample, as well as other adjustments such as the treatment of non-response to the LFS.

A first adjustment was made to the initial weight to reflect that only a sub-sample (i.e., 4 of 6 panels) of the LFS was used. A second adjustment was done to account for the selection of a single household member, 16 years of age or older. The third adjustment started with this interim weight for the sampled individual, and inflated it to represent the non-respondents who did not participate in the CIUS but who did in the LFS. All units selected for the CIUS were modelled using a logistic regression to calculate their propensity to respond. This probability was used to group records into clusters. The inverse of the observed response rate in each cluster was used as the adjustment factor. This adjustment was carried out in three stages: a first step for the CAPI respondents to the LFS who were not interviewed for the CIUS (and in which the propensity to respond via CAPI rather than the propensity to respond was modelled), a second step for the household-level non-respondents where it was not known which member was selected to the CIUS, and a third step for person-level non-respondents where more detailed demographic information could be used in the modelling. The fourth adjustment used Generalized regression (GREG) estimation to calibrate the CIUS weights - matching the age-sex distributions for each province and the population counts for several CMAs. These population projections were taken from the same totals used in the LFS. The final CIUS person-weight is the outcome of these four adjustments to the initial LFS sub-weight.

The quality of the estimates is assessed using estimates of their coefficient of variation (CV). Given the complexity of the CIUS design, CVs cannot be calculated using a simple formula. Bootstrap replicate weights were used to establish the CVs of the estimates.

Quality evaluation

A comparison of social and demographic domains from CIUS was made with the previous survey to ensure consistency. Subject matter experts made selective data confrontations with data from other sources (e.g. the Survey of Household Spending, record number 3508), regulatory agencies (e.g. the Canadian Radio-television and Telecommunications Commission) and international organizations (e.g. the OECD).

After comparing the 2007 Internet use of CATI and CAPI respondents, it was decided to exclude CAPI collection in 2009 and treat by adjusting the weights (see Estimation).

Disclosure control

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.

Users requiring access to information may purchase custom tabulations. Estimates will be released subject to meeting the guidelines for analysis and maintenance of confidentiality.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

The coverage error of the LFS, of which the CIUS is a sub-sample, is estimated at less than 2%. The exclusion of households in which no member is 16 years old or over is considered negligible.

The results estimated from CIUS are based on a sample of Canadians. The CIUS collection response rate was 69% of individuals invited to participate in the CIUS. The CIUS estimation response rate was 61%, taking into account the CIUS nonresponse, the LFS nonresponse and the LFS CAPI cases excluded from CIUS (see Data sources). The results obtained from asking the same questions of all Canadians would differ to some known extent. The extent of this sampling error is quantified by the coefficient of variation (CV) with the following guidelines:

- 16.5% and below Acceptable;
- 16.6% to 33.3% Marginal, with cautionary note; and
- Above 33.3% Unacceptable estimate.

Estimates that do not meet an acceptable level of quality are either flagged for caution or suppressed. CV tables are prepared by Statistics Canada and made available to help users understand the quality of individual estimates. The CVs represented in the CV look-up table (please see link below) are derived from a key survey variable: PU_Q01 Did you use the Internet during the past 12 months for personal non-business use?

Documentation

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