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Description: The newsletter offers information aimed at three main groups, businesses (small to medium), communities and ethno-cultural groups/communities. Articles and outreach materials will assist their understanding of national and local data from the many relevant sources found on the Statistics Canada website.

Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality.

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This paper introduces and explains modifications made to the Labour Force Survey estimates.

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The Public-Use Microdata File (PUMF) for the Survey of Household Spending (SHS) provides information on household expenditures as well as selected information on dwelling characteristics and household equipment. The production of this file includes many safeguards to prevent the identification of any one person or household.

PUMFs were produced on an annual basis for SHS 1997 to 2009, before a redesigned survey was introduced with the 2010 reference year. The SHS 2017 PUMF is the first SHS PUMF based on data collected after the 2010 survey redesign.

Due to changes to data collection, processing and estimation methods introduced with the 2010 redesign, users are advised not to compare data from SHS 1997 to 2009 with data from any subsequent years, unless otherwise noted.

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This American Sign Language video provides an introduction to the Canadian Survey on Disability. Specifically, it includes a brief description of the benefits of participating in the survey, what participating in the survey involves, how respondents were selected to participate, and information on privacy and confidentiality.

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This infographic explains the steps involved in collecting data for all Statistics Canada household and business surveys. The responses are compiled, analyzed and used to make important decisions and are kept strictly confidential.

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The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and includes topics such as survey methodology, data collection, processing, and data quality.

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Data gathering involves first determining what data you need, then where to find it, how to get it and how to keep it safe. This module introduces you to things you should consider when gathering data.

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The Guide to the Labour Force Survey contains a dictionary of concepts and definitions and covers topics such as survey methodology, data collection, data processing and data quality. It also contains information on products and services, sub-provincial geography descriptions as well as the survey questionnaire.

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This document brings together guidelines and checklists on many issues that need to be considered in the pursuit of quality objectives in the execution of statistical activities. Its focus is on how to assure quality through effective and appropriate design or redesign of a statistical project or program from inception through to data evaluation, dissemination and documentation. These guidelines draw on the collective knowledge and experience of many Statistics Canada employees. It is expected that Quality Guidelines will be useful to staff engaged in the planning and design of surveys and other statistical projects, as well as to those who evaluate and analyze the outputs of these projects.

Description:

The Public-Use Microdata File (PUMF) for the Survey of Household Spending (SHS) provides information on household expenditures as well as selected information on dwelling characteristics and household equipment. The production of this file includes many safeguards to prevent the identification of any one person or household.

PUMFs were produced on an annual basis for SHS 1997 to 2009, before a redesigned survey was introduced with the 2010 reference year. The SHS 2017 PUMF is the first SHS PUMF based on data collected after the 2010 survey redesign.

Due to changes to data collection, processing and estimation methods introduced with the 2010 redesign, users are advised not to compare data from SHS 1997 to 2009 with data from any subsequent years, unless otherwise noted.

Description: The Canadian Tobacco, Alcohol and Drugs Survey (CTADS) is a biennial general population survey of tobacco, alcohol and drug use among Canadians aged 15 years and older, with the primary focus on 15- to 24-year-olds. The CTADS is a telephone survey conducted by Statistics Canada on behalf of Health Canada.

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Statistics Canada was approached by Stentor Resource Centre Incorporated to conduct a survey to monitor the telephone penetration rates across Canada. The survey determines if the respondents have a telephone line in their residence. If they do not have a telephone line, information is collected as to the reasons why. Information is also collected on the income characteristics of the selected households.

The management of the survey was transferred from Stentor to Bell Canada in the Fall of 1998.

The Labour Force Survey (LFS) supplementary capacity is used to conduct this biannual survey. A sample of approximately 44,000 respondents is used for this survey (five out of six rotation groups). The survey data are collected using Computer Assisted Interviewing (CAI). The first data collection procedure took place during November's LFS week in 1996.

This microdata file is prepared biannually and contains the variables from the survey, plus geographical variables from the LFS (province, census metropolitan area, urban/rural breakdown). No other variables from the LFS are added to the file.

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This product provides an overview of trends in the surveying and mapping services industry. It provides users with information required for making corporate decisions, monitoring programs and reviewing policies. The tables focus on financial and operating data.

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This topic presents data on education, labour, place of work, commuting to work and language of work in Canada. The topic presents data on the paid work of the Canadian workforce, including detailed industry and occupation data, class of worker, and work activity during the reference year. Data on workers' place of work and journey to work are also included.

This topic also presents data on four main education concepts: completed education credentials, major field of study, location of study and attendance at school.

Together, these data provide information on education and the work activities of Canadians.

Analytical products

The analytical document provides analysis on the key findings in the data, and is complimented with the short articles found in NHS in Brief and the data in NHS Focus on Geography Series.

Data products

The NHS Profile is one data product that provides a statistical overview of user selected geographic areas based on several detailed variables and/or groups of variables. Other data products include data tables which represent a series of cross tabulations ranging in complexity and are available for various levels of geography.

Description:

This product, offered on CD-ROM, contains the public microdata for the Adult Literacy and Life Skills Survey.

The Adult Literacy and Life Skills Survey (ALL) is a large-scale co-operative effort undertaken in 2003, 2006 and 2008 by governments, national statistics agencies, research institutions and multi-lateral agencies. The ALL study builds on the International Adult Literacy Survey (IALS),the world's first internationally comparative survey of adult skills undertaken in three rounds of data collection between 1994 and 1998.

The foundation skills measured in the ALL survey include prose literacy, document literacy, numeracy and problem solving. Additional skills assessed indirectly include familiarity with and use of information and communication technologies.

The development and management of the study were co-ordinated by Statistics Canada and the Educational Testing Service (ETS) in collaboration with the National Center for Education Statistics (NCES) of the United States Department of Education, the Organisation for Economic Cooperation and Development (OECD), the Regional Office for Latin America and the Caribbean (OREALC) and the Institute for Statistics (UIS) of the United Nations Educational, Scientific and Cultural Organisation (UNESCO).

This dataset is composed of seven countries or regions that collected data in 2003. They include Bermuda, Canada, Italy, Norway, Switzerland, the United States and the Mexican State of Nuevo Leon. Additionally data is included for three other countries that collected data in 2006 and 2008 which are Hungary, Netherlands, and New Zealand.

Description: This report details the methodology and results of the Farm Environmental Management Survey (FEMS).

The FEMS is conducted to gather information about farming practices on Canadian crop and livestock operations. The survey focuses on information related to manure storage and spreading, pesticide application, crop and nutrient management, grazing and the implementation of environmental farm plans.

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This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.

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This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.

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This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.

Description: The newsletter offers information aimed at three main groups, businesses (small to medium), communities and ethno-cultural groups/communities. Articles and outreach materials will assist their understanding of national and local data from the many relevant sources found on the Statistics Canada website.

Description:

This American Sign Language video provides an introduction to the Canadian Survey on Disability. Specifically, it includes a brief description of the benefits of participating in the survey, what participating in the survey involves, how respondents were selected to participate, and information on privacy and confidentiality.

Description:

This infographic explains the steps involved in collecting data for all Statistics Canada household and business surveys. The responses are compiled, analyzed and used to make important decisions and are kept strictly confidential.

Description:

Data gathering involves first determining what data you need, then where to find it, how to get it and how to keep it safe. This module introduces you to things you should consider when gathering data.

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This publication is a catalogue of strategies and mechanisms that a statistical organization should consider adopting, according to its particular context. This compendium is based on lessons learned and best practices of leadership and management of statistical agencies within the scope of Statistics Canada’s International Statistical Fellowship Program (ISFP). It contains four broad sections including, characteristics of an effective national statistical system; core management practices; improving, modernizing and finding efficiencies; and, strategies to better inform and engage key stakeholders.

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Careful design of a dual-frame random digit dial (RDD) telephone survey requires selecting from among many options that have varying impacts on cost, precision, and coverage in order to obtain the best possible implementation of the study goals. One such consideration is whether to screen cell-phone households in order to interview cell-phone only (CPO) households and exclude dual-user household, or to take all interviews obtained via the cell-phone sample. We present a framework in which to consider the tradeoffs between these two options and a method to select the optimal design. We derive and discuss the optimum allocation of sample size between the two sampling frames and explore the choice of optimum p, the mixing parameter for the dual-user domain. We illustrate our methods using the National Immunization Survey, sponsored by the Centers for Disease Control and Prevention.

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This infographic demonstrates the journey of data and how respondents' answers to our surveys become useful data used to make informed decisions. The infographic highlights the Labour Force Survey (LFS), the Survey of Household Spending (SHS), and the Canadian Community Health Survey (CCHS).

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This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.

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Composite estimation is a technique applicable to repeated surveys with controlled overlap between successive surveys. This paper examines the modified regression estimators that incorporate information from previous time periods into estimates for the current time period. The range of modified regression estimators are extended to the situation of business surveys with survey frames that change over time, due to the addition of “births” and the deletion of “deaths”. Since the modified regression estimators can deviate from the generalized regression estimator over time, it is proposed to use a compromise modified regression estimator, a weighted average of the modified regression estimator and the generalised regression estimator. A Monte Carlo simulation study shows that the proposed compromise modified regression estimator leads to significant efficiency gains in both the point-in-time and movement estimates.

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This document is for analysts/researchers who are considering doing research with data from a survey where both survey weights and bootstrap weights are provided in the data files. This document gives directions, for some selected software packages, about how to get started in using survey weights and bootstrap weights for an analysis of survey data. We give brief directions for obtaining survey-weighted estimates, bootstrap variance estimates (and other desired error quantities) and some typical test statistics for each software package in turn. While these directions are provided just for the chosen examples, there will be information about the range of weighted and bootstrapped analyses that can be carried out by each software package.

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Often, the same information is gathered almost simultaneously for several different surveys. In France, this practice is institutionalized for household surveys that have a common set of demographic variables, i.e., employment, residence and income. These variables are important co-factors for the variables of interest in each survey, and if used carefully, can reinforce the estimates derived from each survey. Techniques for calibrating uncertain data can apply naturally in this context. This involves finding the best unbiased estimator in common variables and calibrating each survey based on that estimator. The estimator thus obtained in each survey is always a linear estimator, the weightings of which can be easily explained and the variance can be obtained with no new problems, as can the variance estimate. To supplement the list of regression estimators, this technique can also be seen as a ridge-regression estimator, or as a Bayesian-regression estimator.

Description:

The U.S. Consumer Expenditure Survey uses two instruments, a diary and an in-person interview, to collect data on many categories of consumer expenditures. Consequently, it is important to use these data efficiently to estimate mean expenditures and related parameters. Three options are: (1) use only data from the diary source; (2) Use only data from the interview source; and (3) use generalized least squares, or related methods, to combine the diary and interview data. Historically, the U.S. Bureau of Labor Statistics has focused on options (1) and (2) for estimation at the five or six-digit Universal Classification Code level. Evaluation and possible implementation of option (3) depends on several factors, including possible measurement biases in the diary and interview data; the empirical magnitude of these biases, relative to the standard errors of customary mean estimators; and the degree of homogeneity of these biases across strata and periods. This paper reviews some issues related to options (1) through (3); describes a relatively simple generalized least squares method for implementation of option (3); and discussed the need for diagnostics to evaluate the feasibility and relative efficiency of the generalized least squares method.

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The artificial sample was generated in two steps. The first step, based on a master panel, was a Multiple Correspondence Analysis (MCA) carried out on basic variables. Then, "dummy" individuals were generated randomly using the distribution of each "significant" factor in the analysis. Finally, for each individual, a value was generated for each basic variable most closely linked to one of the previous factors. This method ensured that sets of variables were drawn independently. The second step consisted in grafting some other data bases, based on certain property requirements. A variable was generated to be added on the basis of its estimated distribution, using a generalized linear model for common variables and those already added. The same procedure was then used to graft the other samples. This method was applied to the generation of an artificial sample taken from two surveys. The artificial sample that was generated was validated using sample comparison testing. The results were positive, demonstrating the feasibility of this method.

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This user's guide provides a detailed description of the CD-ROM Income trends in Canada (13F0022XCB). It also provides a glossary, a description of the major concepts as well as an overview of the data source, the Survey of Consumer Finances.

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This report deals with sampling and weighting, a process whereby certain characteristics are collected and processed for a random sample of dwellings and persons identified in the complete census enumeration. Data for the whole population are then obtained by scaling up the results for the sample to the full population level. The use of sampling may lead to substantial reductions in costs and respondent burden, or alternatively, can allow the scope of a census to be broadened at the same cost.

Description:

The National Population Health Survey (NPHS) is a family of surveys with multiple objectives, one of which is to provide information on a panel of people who will be followed over time to reflect the dynamic process of health and illness. Data for the first cycle of the NPHS - Households Survey were collected from June 1994 to June 1995, and were released in September 1995. Data for the second cycle were collected from June 1996 to August 1997. One of the primary outputs for the second cycle is a longitudinal master file. This paper will describe six major strategies that were developed to process the longitudinal master file.

Description:

In 1994, Statistics Canada introduced a new longitudinal social survey that collects information from about 23,000 children spread over 13,500 households. The objective of the National Longitudinal Survey of Children and Youth is to measure the development and well being of children until they reach adulthood. To this end, the survey gathers together information about the child, parents, neighbourhood as well as family and school environment. As a consequence, the data collected for each child, is provided by several respondents, from parents to teachers, a situation which contributes to an increased disclosure risk. In order to reach a balance between confidentiality and the analytical value of released data, the survey produces three different microdata files with more or less information. The master file that contains all the information is only available by means of remote access. Hence, researchers do not have direct access to the data, but send their request in the form of software programs that are submitted by Statistics Canada staff. The results are then vetted for confidentiality and sent back to the researchers. The presentation will be devoted to the various disclosure risks of such a survey and to the tools used to reduce those risks.

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In epidemiology analysis of longitudinal data is commonly accepted as providing the most robust measures of association between putative risk and selected outcomes such as death or cancer. SMARTIE is a SAS application for efficient analysis of longitudinal data. Based on person days at risk, it can handle multiple exits from and re-entries to risk, and derives outcome measures such as survival rates. Standardised Mortality Ratios (SMRs) and Cancer Incidence Ratios (SIRs). Summary data can be produced in a format easily ported to any modelling package such as Stats 5.0. We discuss the background to its development, the overall program structure, its command language, and finally we say something about the organization of outputs. Findings from survival studies using the Longitudinal Study of the Office for National Statistics (ONS) are used to demonstrate features of SMARTIE. This study is based on one per cent of the population of England and Wales. It is continually updated with the addition of new members and with information from birth, death and cancer records, and from the census.

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Models for fitting longitudinal binary responses are explored using a panel study of voting intentions. A standard repeated measures multilevel logistic model is shown inadequate due to the presence of a substantial proportion of respondents who maintain a constant response over time. A multivariate binary response model is shown a better fit to the data.

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Longitudinal studies with repeated observations on individuals permit better characterizations of change and assessment of possible risk factors, but there has been little experience applying sophisticated models for longitudinal data to the complex survey setting. We present results from a comparison of different variance estimation methods for random effects models of change in cognitive function among older adults. The sample design is a stratified sample of people 65 and older, drawn as part of a community-based study designed to examine risk factors for dementia. The model summarizes the population heterogeneity in overall level and rate of change in cognitive function using random effects for intercept and slope. We discuss an unweighted regression including covariates for the stratification variables, a weighted regression, and bootstrapping; we also did preliminary work into using balanced repeated replication and jackknife repeated replication.