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Survey or statistical program
- Census of Population (4)
- Survey of Household Spending (3)
- Quarterly Demographic Estimates (3)
- Annual Demographic Estimates: Canada, Provinces and Territories (3)
- Estimates of population, by marital status or legal marital Status, age and sex for July 1, Canada, provinces and territories (3)
- Vital Statistics - Birth Database (2)
- Vital Statistics - Death Database (2)
- Estimates of the number of census families for July 1st, Canada, provinces and territories (2)
- Indigenous Peoples Survey (1)
- Annual Demographic Estimates : Subprovincial Areas (1)
- Survey of Labour and Income Dynamics (1)
- Youth Smoking Survey (1)
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All (51)
All (51) (0 to 10 of 51 results)
- Articles and reports: 12-001-X202300200005Description: Population undercoverage is one of the main hurdles faced by statistical analysis with non-probability survey samples. We discuss two typical scenarios of undercoverage, namely, stochastic undercoverage and deterministic undercoverage. We argue that existing estimation methods under the positivity assumption on the propensity scores (i.e., the participation probabilities) can be directly applied to handle the scenario of stochastic undercoverage. We explore strategies for mitigating biases in estimating the mean of the target population under deterministic undercoverage. In particular, we examine a split population approach based on a convex hull formulation, and construct estimators with reduced biases. A doubly robust estimator can be constructed if a followup subsample of the reference probability survey with measurements on the study variable becomes feasible. Performances of six competing estimators are investigated through a simulation study and issues which require further investigation are briefly discussed.Release date: 2024-01-03
- Journals and periodicals: 62F0026MDescription: This series provides detailed documentation on the issues, concepts, methodology, data quality and other relevant research related to household expenditures from the Survey of Household Spending, the Homeowner Repair and Renovation Survey and the Food Expenditure Survey.Release date: 2023-10-18
- Table: 91-002-XDescription:
This publication presents quarterly estimates of population for Canada, provinces and territories as well as statistics on the following components of population change: births, deaths, immigration, emigration, returning emigration, net temporary emigration, net non-permanent residents and interprovincial migration, the latter by origin and destination. The Quarterly Demographic Estimates publication contains the most recent estimates as well as a quarterly historical series. It also contains highlights and analysis of the most current demographic trends, as well as a brief description of the concepts, methods and data quality of the estimates.
Release date: 2022-09-28 - Articles and reports: 12-001-X202100200008Description:
Multiple-frame surveys, in which independent probability samples are selected from each of Q sampling frames, have long been used to improve coverage, to reduce costs, or to increase sample sizes for subpopulations of interest. Much of the theory has been developed assuming that (1) the union of the frames covers the population of interest, (2) a full-response probability sample is selected from each frame, (3) the variables of interest are measured in each sample with no measurement error, and (4) sufficient information exists to account for frame overlap when computing estimates. After reviewing design, estimation, and calibration for traditional multiple-frame surveys, I consider modifications of the assumptions that allow a multiple-frame structure to serve as an organizing principle for other data combination methods such as mass imputation, sample matching, small area estimation, and capture-recapture estimation. Finally, I discuss how results from multiple-frame survey research can be used when designing and evaluating data collection systems that integrate multiple sources of data.
Release date: 2022-01-06 - Articles and reports: 91F0015M2020003Description:
This article paints a portrait of census coverage levels from 1991 to 2016 through the examination of net census undercoverage rates. It reveals that CNU rates are relatively low and stable over time. However, CNU rates fluctuate based on population characteristics. These rates are higher among young adults, particularly men, individuals who live in the territories or on Indian reserves, those who are separated or single, and those whose mother tongue is a language other than English or French. Canadian CNU rates and the characteristics of harder-to-enumerate populations are similar to what is observed internationally.
Release date: 2021-01-26 - Articles and reports: 12-001-X201600114540Description:
In this paper, we compare the EBLUP and pseudo-EBLUP estimators for small area estimation under the nested error regression model and three area level model-based estimators using the Fay-Herriot model. We conduct a design-based simulation study to compare the model-based estimators for unit level and area level models under informative and non-informative sampling. In particular, we are interested in the confidence interval coverage rate of the unit level and area level estimators. We also compare the estimators if the model has been misspecified. Our simulation results show that estimators based on the unit level model perform better than those based on the area level. The pseudo-EBLUP estimator is the best among unit level and area level estimators.
Release date: 2016-06-22 - Surveys and statistical programs – Documentation: 91-528-XDescription:
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.
Release date: 2015-11-17 - Articles and reports: 12-001-X201200211754Description:
The propensity-scoring-adjustment approach is commonly used to handle selection bias in survey sampling applications, including unit nonresponse and undercoverage. The propensity score is computed using auxiliary variables observed throughout the sample. We discuss some asymptotic properties of propensity-score-adjusted estimators and derive optimal estimators based on a regression model for the finite population. An optimal propensity-score-adjusted estimator can be implemented using an augmented propensity model. Variance estimation is discussed and the results from two simulation studies are presented.
Release date: 2012-12-19 - Surveys and statistical programs – Documentation: 92-567-XDescription:
The Coverage Technical Report will present the error included in census data that results from persons missed by the 2006 Census or persons enumerated in error. Population coverage errors are one of the most important types of error because they affect not only the accuracy of population counts but also the accuracy of all of the census data describing characteristics of the population universe.
Release date: 2010-03-25 - Surveys and statistical programs – Documentation: 92-569-X2006002Description:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
The second edition includes the same content as the first, and new text has been added on data processing (Chapter 3). As well, modified content about data quality and 'on reserve' communities has been incorporated into the original sections.
Release date: 2010-02-09
Data (3)
Data (3) ((3 results))
- Table: 91-002-XDescription:
This publication presents quarterly estimates of population for Canada, provinces and territories as well as statistics on the following components of population change: births, deaths, immigration, emigration, returning emigration, net temporary emigration, net non-permanent residents and interprovincial migration, the latter by origin and destination. The Quarterly Demographic Estimates publication contains the most recent estimates as well as a quarterly historical series. It also contains highlights and analysis of the most current demographic trends, as well as a brief description of the concepts, methods and data quality of the estimates.
Release date: 2022-09-28 - 2. Annual Demographic Statistics ArchivedTable: 91-213-XDescription:
This publication contains population estimates by age and sex for Canada, provinces, territories, census divisions, census metropolitan areas and economic regions. It also includes, for provinces and territories, estimates by age, sex and marital status as well as estimates for census families.
The estimates are based on the 2001 Census results, which have been adjusted for net census undercoverage. The publication also includes statistics for the demographic components that were used to produce the population estimates (births, deaths, marriages, divorces, immigration, emigration, net temporary emigration, returning emigration, internal migration and non-permanent residents) by age and sex. In addition, the publication contains highlights of current demographic trends and a description of the methodology.
The print version of the publication includes a CD-ROM that provides additional data such as a chronological series of estimates by various levels of geography. With regard to provinces and territories, the estimates date back to 1971 (tables and animated age pyramid), 1986 for census divisions, census metropolitan areas and economic regions as well as census families.
The time series available on the CD-ROM can be easily captured and manipulated by analysts who want to create customized demographic analyses in any spreadsheet program. The population figures can be used, for example, to calculate per-capita rates required for market research, quantitative analysis and planning.
Release date: 2006-04-04 - 3. Youth Smoking Survey ArchivedPublic use microdata: 82M0011XDescription:
The main objective of the 2002 Youth Smoking Survey (YSS) is to provide current information on the smoking behaviour of students in grades 5 to 9 (in Quebec primary school grades 5 and 6 and secondary school grades 1 to 3), and to measure changes that occurred since the last time the survey was conducted in 1994. Additionally, the 2002 survey collected basic data on alcohol and drug use by students in grades 7 to 9 (in Quebec secondary 1 to 3). Results of the Youth Smoking Survey will help with the evaluation of anti-smoking and anti-drug use programs, as well as with the development of new programs.
Release date: 2004-07-14
Analysis (37)
Analysis (37) (30 to 40 of 37 results)
- 31. A multivariate technique for multiply imputing missing values using a sequence of regression models ArchivedArticles and reports: 12-001-X20010015857Description:
This article describes and evaluates a procedure for imputing missing values for a relatively complex data structure when the data are missing at random. The imputations are obtained by fitting a sequence of regression models and drawing values from the corresponding predictive distributions. The types of regression models used are linear, logistic, Poisson, generalized logit or a mixture of these depending on the type of variable being imputed. Two additional common features in the imputation process are incorporated: restriction to a relevant subpopulation for some variables and logical bounds or constraints for the imputed values. The restrictions involve subsetting the sample individuals that satisfy certain criteria while fitting the regression models. The bounds involve drawing values from a truncated predictive distribution. The development of this method was partly motivated by the analysis of two data sets which are used as illustrations. The sequential regression procedure is applied to perform multiple imputation analysis for the two applied problems. The sampling properties of inferences from multiply imputed data sets created using the sequential regression method are evaluated through simulated data sets.
Release date: 2001-08-22 - Articles and reports: 12-001-X20000015179Description:
This paper suggests estimating the conditional mean squared error of small area estimators to evaluate their accuracy. This mean squared error is conditional in the sense that it measures the variability with respect to the sampling design for a particular realization of the smoothing model underlying the small area estimators. An unbiased estimators for the conditional mean squared error is easily constructed using Stein's Lemma for the expectation of normal random variables.
Release date: 2000-08-30 - Articles and reports: 91F0015M1998005Geography: CanadaDescription:
All countries that organize censuses have concerns about data quality and coverage error. Different methods have been developed in evaluating the quality of census data and census undercount. Some methods make use of information independent of the census itself, while some others are designed to check the internal consistency of the data. These are expensive and complicated operations.
Given that the population in each country is organized differently and that the administrative structures differ from one country to another, no universal method can be applied. In order to compare the methods and identify their strengths and gaps, Demography Division of Statistics Canada has reviewed the procedures used in four industrialized countries: the United States, the United Kingdom, Australia and, of course, Canada. It appears from this review that demographic analysis can help considerably in the identification of inconsistencies through comparisons of consecutive censuses, while micro-level record linkage and survey based procedures are essential in order to estimate the number of people omitted or counted twice in census collection. The most important conclusion from this review is that demographers and statisticians have to work together in order to evaluate the figures the accuracy of which will always remain questionable.
Release date: 1998-03-27 - Articles and reports: 12-001-X19960022979Description:
This paper empirically compares three estimation methods - regression, restricted regression, and principal person - used in a household survey of consumer expenditures. The three methods are applied to post-stratification which is important in many household surveys to adjust for under-coverage of the target population. Post-stratum population counts are typically available from an external census for numbers of persons but not for numbers of households. If household estimates are needed, a single weight must be assigned to each household while using the person counts for post-stratification. This is easily accomplished with regression estimators of totals or means by using person counts in each household's auxiliary data. Restricted regression estimation refines the weights by controlling extremes and can produce estimators with lower variance than Horvitz-Thompson estimators while still adhering to the population controls. The regression methods also allow controls to be used for both person-level counts and quantitative auxiliaries. With the principal person method, persons are classified into post-strata and person weights are ratio adjusted to achieve population control totals. This leads to each person in a household potentially having a different weight. The weight associated with the "principal person" is then selected as the household weight. We will compare estimated means from the three methods and their estimated standard errors for a number of expenditures from the Consumer Expenditure survey sponsored by the U.S. Bureau of Labor Statistics.
Release date: 1997-01-30 - Articles and reports: 12-001-X199500114411Description:
In 1991, Statistics Canada for the first time adjusted the Population Estimates Program for undercoverage in the 1991 Census. The Census coverage studies provided reliable estimates of undercoverage at the provincial level and for national estimates of large age - sex domains. However, the population series required estimates of undercoverage for age - sex domains within each province and territory. Since the direct survey estimates for some of these small domains had large standard errors due to the small sample size in the domain, small area modelling techniques were needed. In order to incorporate the varying degrees of reliability of the direct survey estimates, a regression model utilizing an Empirical Bayes methodology was used to estimate the undercoverage in small domains. A raking ratio procedure was then applied to the undercoverage estimates to preserve consistency with the marginal direct survey estimates. The results of this modelling process are shown along with the estimated reduction in standard errors.
Release date: 1995-06-15 - Articles and reports: 12-001-X199200114496Description:
The Population Estimates Program of Statistics Canada has traditionally been benchmarked to the most recent census, with no allowance for census coverage error. Because of a significant increase in the level of undercoverage in the 1986 Census, however, Statistics Canada is considering the possibility of adjusting the base population of the estimates program for net census undercoverage. This paper develops and compares four estimators of such a base population: the unadjusted census counts, the adjusted census counts, a preliminary test estimator, and a composite estimator. A generalization of previously-proposed risk functions, known as the Weighted Mean Square Error (WMSE), is used as the basis of comparison. The WMSE applies not only to population totals, but to functions of population totals such as population shares and growth rates between censuses. The use of the WMSE to develop and evaluate small-area estimators in the context of census adjustment is also described.
Release date: 1992-06-15 - 37. Reverse record check: Tracing people in Canada ArchivedArticles and reports: 12-001-X198000154835Description:
The Reverse Record Check is the main vehicle used to assess the level of undercoverage in the Canadian Census of Population. A sample of persons is selected from sources independent of the current census and extensive tracing operations are undertaken to determine the usual address of each selected person as of Census day. Census records are then checked to determine whether or not each selected person was enumerated. The tracing is by far the most complex, costly and time-consuming operation associated with this study. It involves extensive use of administrative records as well as tracing in the field. This paper describes the various tracing methods used as well as the success obtained from each of them.
Release date: 1980-06-16
Reference (11)
Reference (11) (0 to 10 of 11 results)
- Surveys and statistical programs – Documentation: 91-528-XDescription:
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.
Release date: 2015-11-17 - Surveys and statistical programs – Documentation: 92-567-XDescription:
The Coverage Technical Report will present the error included in census data that results from persons missed by the 2006 Census or persons enumerated in error. Population coverage errors are one of the most important types of error because they affect not only the accuracy of population counts but also the accuracy of all of the census data describing characteristics of the population universe.
Release date: 2010-03-25 - Surveys and statistical programs – Documentation: 92-569-X2006002Description:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
The second edition includes the same content as the first, and new text has been added on data processing (Chapter 3). As well, modified content about data quality and 'on reserve' communities has been incorporated into the original sections.
Release date: 2010-02-09 - 4. Aboriginal Peoples Technical Report, 2006 Census ArchivedSurveys and statistical programs – Documentation: 92-569-XDescription:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
Release date: 2010-02-09 - Surveys and statistical programs – Documentation: 62F0026M2005006Description:
This report describes the quality indicators produced for the 2003 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2005-10-06 - Surveys and statistical programs – Documentation: 92-393-XDescription:
This report is a brief guide to users of census income data. It provides a general description of the various 2001 Census phases, from data collection, through processing for non-response, to dissemination. Descriptions of, and summary data on, the changes to income data that occurred during the processing stages are given. Comparative data from national accounts and tax data sources at a highly aggregated level are also presented to put the quality of the 2001 Census income data into perspective. For users wishing to compare census income data over time, changes in income content and universe coverage over the years are explained. Finally, a complete description of all census products containing income data is also supplied.
Release date: 2004-09-16 - Surveys and statistical programs – Documentation: 62F0026M2004001Description:
This report describes the quality indicators produced for the 2002 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2004-09-15 - Surveys and statistical programs – Documentation: 62F0026M2002001Description:
This report describes the quality indicators produced for the 2000 Survey of Household Spending. It covers the usual quality indicators that help users interpret the data, such as coefficients of variation, non-response rates, slippage rates and imputation rates.
Release date: 2002-06-28 - 9. A donor imputation system to create a census database fully adjusted for underenumeration ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015668Description:
Following the problems with estimating underenumeration in the 1991 Census of England and Wales the aim for the 2001 Census is to create a database that is fully adjusted to net underenumeration. To achieve this, the paper investigates weighted donor imputation methodology that utilises information from both the census and census coverage survey (CCS). The US Census Bureau has considered a similar approach for their 2000 Census (see Isaki et al 1998). The proposed procedure distinguishes between individuals who are not counted by the census because their household is missed and those who are missed in counted households. Census data is linked to data from the CCS. Multinomial logistic regression is used to estimate the probabilities that households are missed by the census and the probabilities that individuals are missed in counted households. Household and individual coverage weights are constructed from the estimated probabilities and these feed into the donor imputation procedure.
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19990015682Description:
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.
Release date: 2000-03-02
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