Keyword search

Description:

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.

Description:

This overview document describes the conceptual underpinnings of the Integrated Business Statistics Program and explains how program components facilitate a more integrated approach to economic surveying at Statistics Canada.

Description:

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.

Description:

Statistics Canada's Newsletter for Small and Medium-sized Businesses offers information to the business community about Statistics Canada's data and services. The newsletter also offers links to data releases of the Census and National Household Survey, videos, tutorials, media advisories, learning sessions and presentations.

Description:

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.

Description:

Environment Accounts and Statistics Division is Statistics Canada's focal point for the collection, analysis and dissemination of environmental information. This reference guide briefly describes the division's programs, as well as all publications and electronic products offered on a quarterly, annual, biennial and occasional basis.

Description:

The Aboriginal Peoples Survey (APS) is a national survey on the social and economic conditions of First Nations people living off reserve, Métis and Inuit aged 6 years and over. The 2012 APS represents the fourth cycle of the survey and focuses on issues of education, employment and health.

The 2012 APS Concepts and Methods Guide is designed to assist data users by providing relevant information on survey content and concepts, sampling design, collection methods, data processing, data quality and product availability. Chapter 1 introduces the survey's background and objectives; Chapter 2 gives important definitions and describes the survey's themes; Chapters 3 through 5 explain the APS design and outline the data collection and processing steps; Chapter 6 describes the weighting method used; Chapters 7 and 8 review data quality and address comparability of the 2012 APS data with data from other sources; Chapter 9 lists survey products including analytical articles, data tables and reference material; Appendices provide additional definitions and links to other relevant documentation.

Description:

At national statistical institutes experiments embedded in ongoing sample surveys are frequently conducted, for example to test the effect of modifications in the survey process on the main parameter estimates of the survey, to quantify the effect of alternative survey implementations on these estimates, or to obtain insight into the various sources of non-sampling errors. A design-based analysis procedure for factorial completely randomized designs and factorial randomized block designs embedded in probability samples is proposed in this paper. Design-based Wald statistics are developed to test whether estimated population parameters, like means, totals and ratios of two population totals, that are observed under the different treatment combinations of the experiment are significantly different. The methods are illustrated with a real life application of an experiment embedded in the Dutch Labor Force Survey.

Description:

Regression models are routinely used in the analysis of survey data, where one common issue of interest is to identify influential factors that are associated with certain behavioral, social, or economic indices within a target population. When data are collected through complex surveys, the properties of classical variable selection approaches developed in i.i.d. non-survey settings need to be re-examined. In this paper, we derive a pseudo-likelihood-based BIC criterion for variable selection in the analysis of survey data and suggest a sample-based penalized likelihood approach for its implementation. The sampling weights are appropriately assigned to correct the biased selection result caused by the distortion between the sample and the target population. Under a joint randomization framework, we establish the consistency of the proposed selection procedure. The finite-sample performance of the approach is assessed through analysis and computer simulations based on data from the hypertension component of the 2009 Survey on Living with Chronic Diseases in Canada.

Description:

Web surveys are generally connected with low response rates. Common suggestions in textbooks on Web survey research highlight the importance of the welcome screen in encouraging respondents to take part. The importance of this screen has been empirically proven in research, showing that most respondents breakoff at the welcome screen. However, there has been little research on the effect of the design of this screen on the level of the breakoff rate. In a study conducted at the University of Konstanz, three experimental treatments were added to a survey of the first-year student population (2,629 students) to assess the impact of different design features of this screen on the breakoff rates. The methodological experiments included varying the background color of the welcome screen, varying the promised task duration on this first screen, and varying the length of the information provided on the welcome screen explaining the privacy rights of the respondents. The analyses show that the longer stated length and the more attention given to explaining privacy rights on the welcome screen, the fewer respondents started and completed the survey. However, the use of a different background color does not result in the expected significant difference.

Description: The public use microdata file from the 2010 Canada Survey of Giving, Volunteering and Participating is now available. This file contains information collected from nearly 15,000 respondents aged 15 and over residing in private households in the provinces.The public use microdata file provides provincial-level information about the ways in which Canadians donate money and in-kind gifts to charitable and nonprofit organizations; volunteer their time to these organizations; provide help directly to others. Socio-demographic, income and labour force data are also included on the file.

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.

Description:

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.

Description:

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.

Description:

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: Governments and other stakeholders are increasingly interested in assessing the skills of their adult populations in order to monitor how well prepared they are for the challenges of the modern knowledge-based society. Adults are expected to use information in complex ways and to maintain and enhance their literacy skills to adapt to ever changing technologies. Literacy is important not only for personal development, but also for positive educational, social, and economic outcomes. Adult literacy, numeracy and problem-solving skills encompass a continuum of learning that enables individuals to achieve their goals, develop their knowledge and potential, and participate fully in their communities and society as a whole.

Canada has been participating in adult skills assessment surveys for several decades. The surveys are repeated every ten years, with the first in the series taking place in 1994. First there was the International Adult Literacy Survey (IALS), then the International Adult Literacy and Skills Survey (IALSS) in 2003 and the Programme for the International Assessment of Adult Competencies (PIAAC) cycles 1 and 2 in 2012 and 2022 respectively. Each of these surveys builds on the concepts of the previous surveys. Over the years, the framework has broadened the definition of literacy to adapt it to the information age, notably by including reading skills in digital environments.

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.

Description:

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

Description:

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.

Description:

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.

Description:

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.

Description:

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).

Description:

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.

Description:

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.

Description:

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.

Description:

This guide presents information of interest to users of data from the Survey of Household Spending. Data are collected via personal interviews conducted in January, February and March after the reference year using a paper questionnaire. Information is gathered about the spending habits, dwelling characteristics and household equipment of Canadian households during the reference year. The survey covers private households in the ten provinces and three territories. (The three territories are surveyed every second year.)

This guide includes definitions of survey terms and variables and descriptions of survey methodology and data quality. There is also a section describing the various statistics that can be created using expenditure data (e.g., budget share, market share, and aggregates).

Description:

Starting with the 1997 survey year, the Family Expenditure Survey was replaced by the Survey of Household Spending (SHS). This note provides information to users and prospective users of data from the SHS about the differences between the SHS and the former Family Expenditure Survey. Topics covered include sample size, number of questions, coverage, and concepts.

Description:

Starting with the 1997 survey year, the Household Facilities and Equipment Survey was replaced by the Survey of Household Spending (SHS). This note provides information to users and prospective users of data from the SHS about the differences between the SHS and the former Household Facilities and Equipment Survey. Topics covered include sample size, weighting, collection method, reference period, and concepts.

Description:

This report provides an overview of an inventory of publicly available data on the nonprofit sector.

Description:

Direct measures of skill attainment such as the International Adult Literacy Survey are used to assess the importance of educational outcome skills such as literacy in determining labour market outcomes such as earnings. Policy makers also use them to direct resources most efficiently. However, these skill measures are the product of complex statistical procedures. This paper examines the mathematical robustness of the International Adult Literacy Survey measures against other possibilities in estimating the impact of literacy on individual earnings.

Description:

The focus of Symposium'99 is on techniques and methods for combining data from different sources and on analysis of the resulting data sets. In this talk we illustrate the usefulness of taking such an "integrating" approach when tackling a complex statistical problem. The problem itself is easily described - it is how to approximate, as closely as possible, a "perfect census", and in particular, how to obtain census counts that are "free" of underenumeration. Typically, underenumeration is estimated by carrying out a post enumeration survey (PES) following the census. In the UK in 1991 the PEF failed to identify the full size of the underenumeration and so demographic methods were used to estimate the extent of the undercount. The problems with the "traditional" PES approach in 1991 resulted in a joint research project between the Office for National Statistics and the Department of Social Statistics at the University of Southampton aimed at developing a methodology which will allow a "One Number Census" in the UK in 2001. That is, underenumeration will be accounted for not just at high levels of aggregation, but right down to the lowest levels at which census tabulations are produced. In this way all census outputs will be internally consistent, adding to the national population estimates. The basis of this methodology is the integration of information from a number of data sources in order to achieve this "One Number".

Description:

One method of enriching survey data is to supplement information collected directly from the respondent with that obtained from administrative systems. The aims of such a practice include being able to collect data which might not otherwise be possible, provision of better quality information for data items which respondents may not be able to report accurately (or not at all) reduction of respondent load, and maximising the utility of information held in administrative systems. Given the direct link with administrative information, the data set resulting from such techniques is potentially a powerful basis for policy-relevant analysis and evaluation. However, the processes involved in effectively combining data from different sources raise a number of challenges which need to be addressed by the parties involved. These include issues associated with privacy, data linking, data quality, estimation, and dissemination.

Description:

To reach their target audience efficiently, advertisers and media planners need information on which media their customers use. For instance, they may need to know what percentage of Diet Coke drinkers watch Baywatch, or how many AT&T customers have seen an advertisement for Sprint during the last week. All the relevant data could theoretically be collected from each respondent. However, obtaining full detailed and accurate information would be very expensive. It would also impose a heavy respondent burden under current data collection technology. This information is currently collected through separate surveys in New Zealand and in many other countries. Exposure to the major media is measured continuously, and product usage studies are common. Statistical matching techniques provide a way of combining these separate information sources. The New Zealand television ratings database was combined with a syndicated survey of print readership and product usage, using statistical matching. The resulting Panorama service meets the targeting information needs of advertisers and media planners. It has since been duplicated in Australia. This paper discusses the development of the statistical matching framework for combining these databases, and the heuristics and techniques used. These included an experiment conducted using a screening design to identify important matching variables. Studies evaluating and validating the combined results are also summarized. The following three major evaluation criteria were used; accuracy of combined results, statibility of combined results and the preservation of currency results from the component databases. The paper then discusses how the prerequisites for combining the databases were met. The biggest hurdle at this stage was the differences between the analysis techniques used on the two component databases. Finally, suggestions for developing similar statistical matching systems elsewhere will be given.

Description:

A population needs-based health care resource allocation model was developed and applied using age, sex and health status of populations to measure population need for health care in Ontario. To develop the model, provincial data on self-assessed health and health service utilization by age and sex from 62,413 respondents to the 1990 Ontario Health Survey (OHS) were used in combination with provincial health care expenditure data for the fiscal year 1995/96 by age and sex. The model was limited to the services that were covered in the OHS (general practitioner, specialist physician, optometry, physiotherapy, chiropractic and acute hospital). The distribution of utilization and expenditures between age-sex-health status categories was used to establish appropriate health care resource shares for each age-sex-health status combination. These resource shares were then applied to geographic populations using age, sex and health status data from the OHS together with more recent population estimates to determine the needs-based health care resource allocation for each area. Total dollar allocations were restricted to sum to the 1995/96 provincial budget and were compared with 1995/96 allocations to determine the extent to which Ontario allocations are consistent with the relative needs of the area populations.

Description:

The application of dual system estimation (DSE) to matched Census / Post Enumeration Survey (PES) data in order to measure net undercount is well understood (Hogan, 1993). However, this approach has so far not been used to measure net undercount in the UK. The 2001 PES in the UK will use this methodology. This paper presents the general approach to design and estimation for this PES (the 2001 Census Coverage Survey). The estimation combines DSE with standard ratio and regression estimation. A simulation study using census data from the 1991 Census of England and Wales demonstrates that the ratio model is in general more robust than the regression model.