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Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.

Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.

Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.

Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.

Description: We present design-based Horvitz-Thompson and multiplicity estimators of the population size, as well as of the total and mean of a response variable associated with the elements of a hidden population to be used with the link-tracing sampling variant proposed by Félix-Medina and Thompson (2004). Since the computation of the estimators requires to know the inclusion probabilities of the sampled people, but they are unknown, we propose a Bayesian model which allows us to estimate them, and consequently to compute the estimators of the population parameters. The results of a small numeric study indicate that the performance of the proposed estimators is acceptable.

Description: The Longitudinal Social Data Development Program (LSDDP) is a social data integration approach aimed at providing longitudinal analytical opportunities without imposing additional burden on respondents. The LSDDP uses a multitude of signals from different data sources for the same individual, which helps to better understand their interactions and track changes over time. This article looks at how the ethnicity status of people in Canada can be estimated at the most detailed disaggregated level possible using the results from a variety of business rules applied to linked data and to the LSDDP denominator. It will then show how improvements were obtained using machine learning methods, such as decision trees and random forest techniques.

Description: The validity of survival estimates from cancer registry data depends, in part, on the identification of the deaths of deceased cancer patients. People whose deaths are missed seemingly live on forever and are informally referred to as “immortals”, and their presence in registry data can result in inflated survival estimates. This study assesses the issue of immortals in the Canadian Cancer Registry (CCR) using a recently proposed method that compares the survival of long-term survivors of cancers for which “statistical” cure has been reported with that of similar people from the general population.

Description:

This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.

Description: Microdata files are unique among census products in that they give users access to unaggregated data. This makes the public use microdata files (PUMFs) powerful research tools. Each file contains anonymous individual responses on a large number of variables. The PUMF user can group and manipulate these variables to suit his/her own data and research requirements. Tabulations not included in other census products can be created or relationships between variables can be analysed by using different statistical tests. PUMFs provide quick access to a comprehensive social and economic database about Canada and its people. All subject-matter covered by the census is included in the microdata files. However, to ensure the anonymity of the respondents, geographic identifiers have been restricted to the provinces/territories and large metropolitan areas. Microdata files have traditionally been disseminated on magnetic tape, which required access to a mainframe computer. For the first time, the 1991 PUMFs will also be available on CD-ROM for microcomputer applications. This file contains data based on a 3% of the population enumerated in the 1991 Census. It provides information on the demographic, social and economic characteristics of the Canadian population. The Individual File allows users to return to the base unit of the census, enabling them to group and manipulate the data to suit their own data and research requirements.

This product provides two basic tools to assist users in accessing and using the 1991 Census Public Use Microdata File - Individuals CD-ROM.

Description: Microdata files are unique among census products in that they give users access to unaggregated data. This makes the public use microdata files (PUMFs) powerful research tools. Each file contains anonymous individual responses on a large number of variables. The PUMF user can group and manipulate these variables to suit his/her own data and research requirements. Tabulations not included in other census products can be created or relationships between variables can be analysed by using different statistical tests. PUMFs provide quick access to a comprehensive social and economic database about Canada and its people. All subject-matter covered by the census is included in the microdata files. However, to ensure the anonymity of the respondents, geographic identifiers have been restricted to the provinces/territories and large metropolitan areas. Microdata files have traditionally been disseminated on magnetic tape, which required access to a mainframe computer. For the first time, the 1991 PUMFs will also be available on CD-ROM for microcomputer applications. This file contains data based on a 3% of the population enumerated in the 1991 Census. It provides information on the demographic, social and economic characteristics of the Canadian population. The Households and Housing File allows users to return to the base unit of the census, enabling them to group and manipulate the data to suit their own data and research requirements.

This product provides two basic tools to assist users in accessing and using the 1991 Census Public Use Microdata File - Households and Housing CD-ROM.

Description: Microdata files are unique among census products in that they give users access to unaggregated data. This makes the public use microdata files (PUMFs) powerful research tools. Each file contains anonymous individual responses on a large number of variables. The PUMF user can group and manipulate these variables to suit his/her own data and research requirements. Tabulations not included in other census products can be created or relationships between variables can be analysed by using different statistical tests. PUMFs provide quick access to a comprehensive social and economic database about Canada and its people. All subject-matter covered by the census is included in the microdata files. However, to ensure the anonymity of the respondents, geographic identifiers have been restricted to the provinces/territories and large metropolitan areas. Microdata files have traditionally been disseminated on magnetic tape, which required access to a mainframe computer. For the first time, the 1991 PUMFs will also be available on CD-ROM for microcomputer applications. This file contains data based on a 3% of the population enumerated in the 1991 Census. It provides information on the demographic, social and economic characteristics of the Canadian population. The Individual File allows users to return to the base unit of the census, enabling them to group and manipulate the data to suit their own data and research requirements.

This product provides two basic tools to assist users in accessing and using the 1991 Census Public Use Microdata File - Individuals CD-ROM.

Description: Microdata files are unique among census products in that they give users access to unaggregated data. This makes the public use microdata files (PUMFs) powerful research tools. Each file contains anonymous individual responses on a large number of variables. The PUMF user can group and manipulate these variables to suit his/her own data and research requirements. Tabulations not included in other census products can be created or relationships between variables can be analysed by using different statistical tests. PUMFs provide quick access to a comprehensive social and economic database about Canada and its people. All subject-matter covered by the census is included in the microdata files. However, to ensure the anonymity of the respondents, geographic identifiers have been restricted to the provinces/territories and large metropolitan areas. Microdata files have traditionally been disseminated on magnetic tape, which required access to a mainframe computer. For the first time, the 1991 PUMFs will also be available on CD-ROM for microcomputer applications. This file contains data based on a 3% of the population enumerated in the 1991 Census. It provides information on the demographic, social and economic characteristics of the Canadian population. The Households and Housing File allows users to return to the base unit of the census, enabling them to group and manipulate the data to suit their own data and research requirements.

This product provides two basic tools to assist users in accessing and using the 1991 Census Public Use Microdata File - Households and Housing CD-ROM.

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:

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:

This package was designed to enable users to access and manipulate the microdata file for Cycle 22 (2008) of the General Social Survey (GSS). It contains information on the objectives, methodology and estimation procedures, as well as guidelines for releasing estimates based on the survey. Cycle 22 collected data from persons 15 years and over living in private households in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut; and full-time residents of institutions. The survey covered a range of topics such as social networks, and social and civic participation. Information was also collected on major changes in respondents' lives in the last 12 months, the resources they used during these transitions and unmet needs for help. Questions were also asked on trust, sense of belonging, volunteering and unpaid work.

Description:

The Participation and Activity Limitation Survey (PALS) is a post-censal survey of adults with disabilities, including any person whose everyday activities are limited because of a physical condition or health problem.

The survey covers themes such as activity limitations, help with everyday activities, education, employment status, social participation and economic characteristics.

Description:

This package was designed to enable users to access and manipulate the microdata file for the 21st cycle (2007) of the General Social Survey (GSS). It contains information on the objectives, methodology and estimation procedures, as well as guidelines for releasing estimates based on the survey. Cycle 21 of the GSS collected data from persons aged 45 years and over living in private households in the 10 provinces of Canada. The survey covered a wide range of topics such as well-being, family composition, retirement decisions and plans, care giving and care receiving experiences, social networks and housing.

Description:

The Aboriginal Peoples Survey (APS) provides data on the social and economic conditions of Aboriginal people in Canada. Its specific purpose was to identify the needs of Aboriginal people focusing on issues such as health, schooling and language. The survey was designed and implemented in partnership with national Aboriginal organizations.

This product contains information for the Aboriginal child and youth population (under 15 years) living in off-reserve areas.

Description:

Cycle 16 of the GSS is the second cycle (after cycle 11) to collect information social support for older Canadians, introducing modules on preparations for retirement and retirement experience. The GSS is an annual telephone survey covering the non-institutionalized population in the 10 provinces. Respondents were randomly selected from a list of individuals aged 45 and over who had responded to another Statistics Canada survey. Data were collected over an 11-month period from February to December 2002. The representative sample had about 25,000 respondents. The response rate was almost 84%.

The main objective of the 2002 GSS was to provide data on the aging population. However, the survey allows detailed analysis of characteristics of family and friends who provide care to seniors; characteristics of seniors receiving formal and informal care; links to broader determinants of health (such as income, education and social networks); and people's retirement plans and experiences.

Description:

Topics covered include social contact with friends and relatives, unpaid help given and received, volunteering and charitable giving, civic engagement, political engagement, religious participation, trust and reciprocity. Cycle 17 of the General Social Survey is the first cycle to collect detailed information on social engagement in Canada.

The target population for Cycle 17 is all persons 15 years of age and older in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut, and full-time residents of institutions.

Description:

In the Netherlands, statistical information about income and wealth is based on two large scale household panels that are completely derived from administrative data. A problem with using households as sampling units in the sample design of panels is the instability of these units over time. Changes in the household composition affect the inclusion probabilities required for design-based and model-assisted inference procedures. Such problems are circumvented in the two aforementioned household panels by sampling persons, who are followed over time. At each period the household members of these sampled persons are included in the sample. This is equivalent to sampling with probabilities proportional to household size where households can be selected more than once but with a maximum equal to the number of household members. In this paper properties of this sample design are described and contrasted with the Generalized Weight Share method for indirect sampling (Lavallée 1995, 2007). Methods are illustrated with an application to the Dutch Regional Income Survey.

Description:

The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.

Description:

Self-weighting estimation through equal probability selection methods (epsem) is desirable for variance efficiency. Traditionally, the epsem property for (one phase) two stage designs for estimating population-level parameters is realized by using each primary sampling unit (PSU) population count as the measure of size for PSU selection along with equal sample size allocation per PSU under simple random sampling (SRS) of elementary units. However, when self-weighting estimates are desired for parameters corresponding to multiple domains under a pre-specified sample allocation to domains, Folsom, Potter and Williams (1987) showed that a composite measure of size can be used to select PSUs to obtain epsem designs when besides domain-level PSU counts (i.e., distribution of domain population over PSUs), frame-level domain identifiers for elementary units are also assumed to be available. The term depsem-A will be used to denote such (one phase) two stage designs to obtain domain-level epsem estimation. Folsom et al. also considered two phase two stage designs when domain-level PSU counts are unknown, but whole PSU counts are known. For these designs (to be termed depsem-B) with PSUs selected proportional to the usual size measure (i.e., the total PSU count) at the first stage, all elementary units within each selected PSU are first screened for classification into domains in the first phase of data collection before SRS selection at the second stage. Domain-stratified samples are then selected within PSUs with suitably chosen domain sampling rates such that the desired domain sample sizes are achieved and the resulting design is self-weighting. In this paper, we first present a simple justification of composite measures of size for the depsem-A design and of the domain sampling rates for the depsem-B design. Then, for depsem-A and -B designs, we propose generalizations, first to cases where frame-level domain identifiers for elementary units are not available and domain-level PSU counts are only approximately known from alternative sources, and second to cases where PSU size measures are pre-specified based on other practical and desirable considerations of over- and under-sampling of certain domains. We also present a further generalization in the presence of subsampling of elementary units and nonresponse within selected PSUs at the first phase before selecting phase two elementary units from domains within each selected PSU. This final generalization of depsem-B is illustrated for an area sample of housing units.

Description:

This paper develops allocation methods for stratified sample surveys where composite small area estimators are a priority, and areas are used as strata. Longford (2006) proposed an objective criterion for this situation, based on a weighted combination of the mean squared errors of small area means and a grand mean. Here, we redefine this approach within a model-assisted framework, allowing regressor variables and a more natural interpretation of results using an intra-class correlation parameter. We also consider several uses of power allocation, and allow the placing of other constraints such as maximum relative root mean squared errors for stratum estimators. We find that a simple power allocation can perform very nearly as well as the optimal design even when the objective is to minimize Longford’s (2006) criterion.

Description:

Rotating panels are widely applied by national statistical institutes, for example, to produce official statistics about the labour force. Estimation procedures are generally based on traditional design-based procedures known from classical sampling theory. A major drawback of this class of estimators is that small sample sizes result in large standard errors and that they are not robust for measurement bias. Two examples showing the effects of measurement bias are rotation group bias in rotating panels, and systematic differences in the outcome of a survey due to a major redesign of the underlying process. In this paper we apply a multivariate structural time series model to the Dutch Labour Force Survey to produce model-based figures about the monthly labour force. The model reduces the standard errors of the estimates by taking advantage of sample information collected in previous periods, accounts for rotation group bias and autocorrelation induced by the rotating panel, and models discontinuities due to a survey redesign. Additionally, we discuss the use of correlated auxiliary series in the model to further improve the accuracy of the model estimates. The method is applied by Statistics Netherlands to produce accurate official monthly statistics about the labour force that are consistent over time, despite a redesign of the survey process.

Description:

The problem of optimal allocation of samples in surveys using a stratified sampling plan was first discussed by Neyman in 1934. Since then, many researchers have studied the problem of the sample allocation in multivariate surveys and several methods have been proposed. Basically, these methods are divided into two classes: The first class comprises methods that seek an allocation which minimizes survey costs while keeping the coefficients of variation of estimators of totals below specified thresholds for all survey variables of interest. The second aims to minimize a weighted average of the relative variances of the estimators of totals given a maximum overall sample size or a maximum cost. This paper proposes a new optimization approach for the sample allocation problem in multivariate surveys. This approach is based on a binary integer programming formulation. Several numerical experiments showed that the proposed approach provides efficient solutions to this problem, which improve upon a ‘textbook algorithm’ and can be more efficient than the algorithm by Bethel (1985, 1989).

Description:

An area-level model approach to combining information from several sources is considered in the context of small area estimation. At each small area, several estimates are computed and linked through a system of structural error models. The best linear unbiased predictor of the small area parameter can be computed by the general least squares method. Parameters in the structural error models are estimated using the theory of measurement error models. Estimation of mean squared errors is also discussed. The proposed method is applied to the real problem of labor force surveys in Korea.

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:

A popular area level model used for the estimation of small area means is the Fay-Herriot model. This model involves unobservable random effects for the areas apart from the (fixed) linear regression based on area level covariates. Empirical best linear unbiased predictors of small area means are obtained by estimating the area random effects, and they can be expressed as a weighted average of area-specific direct estimators and regression-synthetic estimators. In some cases the observed data do not support the inclusion of the area random effects in the model. Excluding these area effects leads to the regression-synthetic estimator, that is, a zero weight is attached to the direct estimator. A preliminary test estimator of a small area mean obtained after testing for the presence of area random effects is studied. On the other hand, empirical best linear unbiased predictors of small area means that always give non-zero weights to the direct estimators in all areas together with alternative estimators based on the preliminary test are also studied. The preliminary testing procedure is also used to define new mean squared error estimators of the point estimators of small area means. Results of a limited simulation study show that, for small number of areas, the preliminary testing procedure leads to mean squared error estimators with considerably smaller average absolute relative bias than the usual mean squared error estimators, especially when the variance of the area effects is small relative to the sampling variances.

Description:

Matrix sampling, often referred to as split-questionnaire, is a sampling design that involves dividing a questionnaire into subsets of questions, possibly overlapping, and then administering each subset to one or more different random subsamples of an initial sample. This increasingly appealing design addresses concerns related to data collection costs, respondent burden and data quality, but reduces the number of sample units that are asked each question. A broadened concept of matrix design includes the integration of samples from separate surveys for the benefit of streamlined survey operations and consistency of outputs. For matrix survey sampling with overlapping subsets of questions, we propose an efficient estimation method that exploits correlations among items surveyed in the various subsamples in order to improve the precision of the survey estimates. The proposed method, based on the principle of best linear unbiased estimation, generates composite optimal regression estimators of population totals using a suitable calibration scheme for the sampling weights of the full sample. A variant of this calibration scheme, of more general use, produces composite generalized regression estimators that are also computationally very efficient.

Description:

This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.

Description: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.

Description: This document introduces and describes updates to the Labour Force Survey estimates in January 2023. These updates include the transition to National Occupational Classification (NOC) 2021 as well as enhancements to the LFS data processing system.

Description:

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

Description:

This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2021. Some of these modifications include the adjustment of all LFS estimates to reflect population counts based on the 2016 Census and includes updates to 2016 Geography classification system.

Description:

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:

This manual provides detailed descriptions of the data sources and methods used by Statistics Canada to estimate population. They comprise Postcensal and intercensal population estimates; base population; births and deaths; immigration; emigration; non-permanent residents; interprovincial migration; subprovincial estimates of population; population estimates by age, sex and marital status; and census family estimates. A glossary of principal terms is contained at the end of the manual, followed by the standard notation used.

Until now, literature on the methodological changes for estimates calculations has always been spread throughout various Statistics Canada publications and background papers. This manual provides users of demographic statistics with a comprehensive compilation of the current procedures used by Statistics Canada to prepare population and family estimates.

Description:

This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2015. Some of these modifications include the adjustment of all LFS estimates to reflect population counts based on the 2011 Census and includes updates to 2011 Geography classification system.

Description:

This report describes sampling and weighting procedures used in the 2011 National Household Survey. It provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.

Description: Quantifying how Canada's water yield has changed over time is an important component of the water accounts maintained by Statistics Canada. This study evaluates the movement in the series of annual water yield estimates for Southern Canada from 1971 to 2004. We estimated the movement in the series using a trend-cycle approach and found that water yield for southern Canada has generally decreased over the period of observation.