Household Internet Use Survey

Detailed information for 2003

Status:

Active

Frequency:

Annual

Record number:

4432

The Household Internet Use Survey collects detailed data on the Internet activities of Canadian households.

Data release - July 8, 2004

Description

The Household Internet Use survey results are widely used by policy makers from federal and provincial to shape policies and programmes related to: the uptake and barriers to the adoption and use of the Internet and electronic commerce, the digital divide, high speed access to the Internet, international benchmarking as well as adoption rates and their effect on Government-on-line initiatives.

The file can support a wide range of research, including projects under the SSHRC Initiative for the New Economy.

Microdata is available to students and academics within universities and colleges under the Data Liberation Initiative.

The Organization for Economic Cooperation and Development uses the file to compare adoption and rates for purposes of international comparability.

The file has been widely used in the private sector for calibration of similar research, as well as consultation on issues related to specific uses of the internet.

Results of the HIUS are widely used by the media.

Statistical activity

Science and technology (S&T) and the information society are changing the way we live, learn and work. The concepts are closely intertwined: science generates new understanding of the way the world works, technology applies it to develop innovative products and services and the information society is one of the results of the innovations.

People are looking to Statistics Canada to measure and explain the social and economic impacts of these changes.

The purpose of this Program is to develop useful indicators of S&T activity in Canada based on a framework that ties them together in a coherent picture.

Collection period: LFS interview week, usually the third week of month

Subjects

  • Individual and household internet use
  • Information and communications technology

Data sources and methodology

Target population

All residents of Canada 15 years of age or older excluding:
Residents of the Yukon, Northwest Territories and Nunavut,
Inmates of Institutions,
Persons living on Indian Reserves,
Full time members of the Canadian Armed Forces.
Exclusions constitute 2% of the population, 15 years of age and older.

Instrument design

The questionnaire was designed in consultation with stakeholders as well as Statistics Canada.

Questionnaire content was tested using focus group methodology in May / June 2000.

Sampling

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

The HIUS was administered to a sub-sample of the households in the Labour Force Survey (LFS) sample, and therefore its sample design is closely tied to that of the LFS.

The LFS has undergone an extensive redesign, culminating in the introduction of a new design at the end of 1994. The LFS sample is based upon a stratified, multi-stage design employing probability sampling at all stages of the design. Household samples are drawn for each survey year. Weighting is benchmarked to the Census of Population.

HIUS uses 5 OF 6 LFS rotation groups for the particular month of collection prior to reference year 2003. For reference year 2003, 4 of 6 rotation groups were utilized during collection in January 2004.

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The Household Internet Use Survey (HIUS) is collected as a supplement to the Labour Force Survey (LFS). Information for the HIUS is usually obtained from the LFS reference person.

Upon completion of the Labour Force Survey interview, the interviewer introduces the HIUS and proceeds with the interview with the respondent's permission.

The respondent answers a proxy survey on behalf of all household members.

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

Error detection

On-line edits and post processing are used to ensure data consistency. Outiliers for electronic commerce, number of orders and value are evaluated for consistency and reliability of response. Non response household income is imputed in quartile and quintile variable only.

Imputation

Imputation is the process that supplies valid values for those variables that have been identified for a change because of invalid information or because of missing information.

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 HIUS to item nonresponse for a few variables. Total nonrespondents were dropped from the data file and accounted for in the weighting process. Imputation was performed for the income variable and for some of the e-commerce variables.

Income was obtained from other LFS supplements whenever possible.

Quality evaluation

Comparison to data files such as the General Social Survey -- Cycle 14, Survey of Household Spending as well as validation of concepts and definitions with the Organisation for Economic Co-operation and Development (OECD) were conducted.

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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

Quality assurance measures were implemented at each step of the data collection and processing cycle to monitor the quality of the data.

These measures included the use of highly skilled interviewers, extensive training of interviewers with respect to the survey procedures and questionnaire, observation of interviewers to detect problems of questionnaire design or misunderstanding of instructions, procedures to ensure that data capture errors were minimized and coding and edit quality checks to verify the processing logic.

Tables for coefficient of variation (CV) of individual concepts are provided free of charge within the user guide for each HIUS microdata file. CV tables help users understand quality of individual estimates.

Documentation

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