Survey design
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Survey or statistical program
- Survey of Labour and Income Dynamics (6)
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- Biotechnology Use and Development Survey (1)
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- Longitudinal and International Study of Adults (1)
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All (330)
All (330) (0 to 10 of 330 results)
- Journals and periodicals: 75F0002MDescription: This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.Release date: 2026-05-20
- Articles and reports: 12-001-X202500200013Description: This article examines the methodological complexities associated with the design of business surveys, with particular emphasis on sampling strategies implemented by National Statistical Offices (NSOs). It addresses the inherent challenges posed by the dynamic nature of the business population, which necessitates continual updates to the sampling frame to ensure representativeness and relevance. Critical design considerations include the determination of optimal sample sizes, stratification across key dimensions such as industry, geographic region, and enterprise size, as well as the treatment of business births and the exclusion of inactive (or “dead”) units. The article applies Bankier’s (1988) power allocation method to a two-way stratification scheme defined by industry and geography, evaluating its performance by comparing the resulting coefficients of variation with those obtained via a raking algorithm applied to the marginal coefficients. Furthermore, the approach is extended to a multivariate context to accommodate multiple estimation domains. The discussion also encompasses practical issues related to sample rotation and coordination, which are critical for maintaining data quality and minimizing respondent burden over time.Release date: 2025-12-23
- Articles and reports: 75-005-M2025001Description: Since 2010, engaging Canadians to participate in the LFS has become more challenging due to a variety of social and technological changes. The decline in the LFS response rate accelerated in 2020, exacerbated by public health measures during the COVID-19 pandemic. This technical paper presents preliminary results of two collection initiatives implemented using an online first strategy to improve the LFS response rates by confirming respondent contact information and expanding the availability of online response. Through these and other planned initiatives, Statistics Canada is working to ensure that the LFS estimates continue to provide an accurate and representative portrait of the Canadian labour market.Release date: 2025-10-21
- Articles and reports: 11-522-X202500100004Description: The Survey of Household Spending (SHS) conducted by Statistics Canada collects paper diaries and shopping receipts as a source of household expenditure data. An auto-capturing algorithm was created for SHS 2023 to reduce statistical clerks' manual work of extracting important information from scanned receipts of common store brands. The algorithm used Tesseract optical character recognition (OCR) to extract text characters from images of receipts, and it identified store and product entities using regular expressions, also known as regex. The goal of this study was to enhance the current auto-capture algorithm by experimenting with more advanced OCR and machine learning methods. As a result, PaddleOCR, an open-source OCR toolkit, was selected as the new default OCR engine due to its overall performance in recognizing texts, especially digits, accurately across receipts of various qualities. Additionally, entity classifiers based on support vector machines were trained on historical SHS records and existing regex patterns. By using classifiers to categorize different elements present on receipts instead of relying solely on regex patterns, product and store recognition improved. It is expected that this new algorithm will be used for SHS 2025 to improve the auto-capture quality and reduce the manual burden associated with capturing receipt variables.Release date: 2025-09-08
- 5. Data-driven Imputation Strategies and their Associated Quality Indicators in Economic Surveys ArchivedArticles and reports: 11-522-X202500100011Description: The use of modern "data"-driven imputation methods to treat non-response in the context of surveys processed in the Integrated Business Statistics Program at Statistics Canada has previously been explored. It was observed that these methods can lead to high quality imputation and further have the potential to result in broad efficiencies when setting up a particular survey's edit and imputation strategy. However, estimation of the associated total variance, more specifically the component due to imputation, remains a challenge. In this article, two methods for estimation of total variance are proposed and show preliminary results that have motivated us to pursue further research in this area.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100029Description: J.N.K. Rao has contributed to almost every subdiscipline of survey research, including unequal-probability and two-phase sampling, variance estimation, regression and categorical data analysis, small area estimation, and data integration. For each of these topics, Rao's work anticipated and led future research directions. His contributions will be discussed in the context of broader research trends as seen in the articles of Survey Methodology over the journal's 50-year history.Release date: 2025-09-08
- 7. Contributions of J.N.K. Rao to Complex Survey Multilevel Models and Composite Likelihood ArchivedArticles and reports: 11-522-X202500100030Description: In the setting of multilevel models to be estimated using data from surveys with complex sampling designs, this paper outlines some contributions of the landmark paper by Rao, Verret and Hidiroglou (Survey Methodology, 2013) and subsequent related work.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100032Description: Although non-probability data sources are not new to official statistics, a revived interest in the topic has emerged from pressures due to falling survey response rates, increasing data collection costs and a desire to take advantage of new data source opportunities from the ongoing societal digitalisation. Due to the exclusion of certain segments of the target population, inference derived solely from a non-probability data source is likely to result in bias. This work approaches the challenge of addressing the bias by integrating non-probability data with reference probability samples. The focus will be on methods to model the propensity of inclusion in the non-probability dataset with the help of the accompanying reference sample, with the modelled propensities then applied in an inverse probability weighting approach to produce population estimates. The reference sample is sometimes assumed as given. In this presentation however, an objective of finding an optimal strategy will be pursued that is, the combination of a data integration-based estimator and sample design for the reference probability sample. Recent work is discussed in which advantage is taken of the good unit identification possibilities in business surveys to study an estimator based on propensities and derive optimal (unequal) selection probabilities for the reference sample.Release date: 2025-09-08
- 9. Including Non-binary Gender in the Calibration Strategy for the Canadian Long-Form Sample Survey Weights ArchivedArticles and reports: 11-522-X202500100033Description: Aligning with recent needs for increased disaggregated data, in 2021 Canada became the first country to collect and disseminate data on gender diversity in a national census giving Canadians the option to select male, female, or non-binary. Due to their small size, non-binary population counts were not used in the 2021 Census long-form sample calibration procedure due to the risk of increasing the variance of estimates. This paper presents an alternative long-form calibration strategy which allows for small populations, such as the non-binary group, to be incorporated while mitigating methodological concerns. The strategy put forward can incorporate multiple small populations simultaneously while also being flexible enough to fit the calibration systems of other National Statistical Offices (NSOs). The results of a Monte Carlo (MC) simulation are presented showing improved data quality for the non-binary population under the alternative calibration strategy.Release date: 2025-09-08
- Articles and reports: 12-001-X202500100010Description: The discussants highlight promising research topics for improving the quality and granularity of estimates from surveys. We agree that continued research is needed to evaluate models used for inference, and suggest development of measures of model dependence.Release date: 2025-06-30
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Analysis (301)
Analysis (301) (10 to 20 of 301 results)
- Articles and reports: 12-001-X202500100011Description: This discussion examines some advancements in survey design and estimation, inspired by the comprehensive appraisal of Professors Jon Rao and Sharon Lohr on current trends in the field. It delves into three specific areas: balanced sampling, calibration, and small area estimation. Probabilistic balanced sampling methods, such as the cube method and penalized balanced sampling, are explored, with an emphasis on addressing emerging challenges, including extensions to linear mixed models, nonparametric regression models, and spatially balanced designs. Calibration is discussed using a modular framework that incorporates modern regression techniques, and highlights innovative uses of model calibration for data editing and causal inference. Small area estimation is considered in the context of latent variable modeling and data integration, emphasizing its role when the variable(s) of interest cannot be measured either directly or without error. Applications in integrating probability and non-probability data and conducting causal analysis at local level are also discussed.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100012Description: In this discussion, we complement the excellent overview by Profs. Lohr and Rao with some additional topics. The first topic is a call for more recognition of the central role of modeling in survey estimation. The second is a brief discussion of the use of partial frame information in survey design. Finally, we draw the attention to recent increases of synthetic methods, in particular, multilevel regression and poststratification (MRP) in small area estimation applications.Release date: 2025-06-30
- Articles and reports: 12-001-X202400200003Description: The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified \pi estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository.Release date: 2024-12-20
- Articles and reports: 12-001-X202400200016Description: Joseph Waksberg was an important figure in survey statistics mainly through his applied work in the design of samples. He took a design-based approach to sample design by emphasizing uses of randomization with the goal of creating estimators with good design-based properties. Since his time on the scene, advances have been made in the use of models to construct designs and in software to implement elaborate designs. This paper reviews uses of models in balanced sampling, cutoff samples, stratification using models, multistage sampling, and mathematical programming for determining sample sizes and allocations.Release date: 2024-12-20
- Articles and reports: 75-005-M2024005Description: This article provides information about how wage data is collected in the Labour Force Survey (LFS). In particular, it examines aspects of the LFS methodology which may impact wage trends.Release date: 2024-12-13
- Articles and reports: 75F0002M2024005Description: 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.Release date: 2024-04-26
- 17. Children born into vulnerability: Challenges encountered in a Quebec longitudinal survey ArchivedArticles and reports: 11-522-X202200100010Description: Growing Up in Québec is a longitudinal population survey that began in the spring of 2021 at the Institut de la statistique du Québec. Among the children targeted by this longitudinal follow-up, some will experience developmental difficulties at some point in their lives. Those same children often have characteristics associated with higher sample attrition (low-income family, parents with a low level of education). This article describes the two main challenges we encountered when trying to ensure sufficient representativeness of these children, in both the overall results and the subpopulation analyses.Release date: 2024-03-25
- Articles and reports: 12-001-X202300200001Description: When a Medicare healthcare provider is suspected of billing abuse, a population of payments X made to that provider over a fixed timeframe is isolated. A certified medical reviewer, in a time-consuming process, can determine the overpayment Y = X - (amount justified by the evidence) associated with each payment. Typically, there are too many payments in the population to examine each with care, so a probability sample is selected. The sample overpayments are then used to calculate a 90% lower confidence bound for the total population overpayment. This bound is the amount demanded for recovery from the provider. Unfortunately, classical methods for calculating this bound sometimes fail to provide the 90% confidence level, especially when using a stratified sample. In this paper, 166 redacted samples from Medicare integrity investigations are displayed and described, along with 156 associated payment populations. The 7,588 examined (Y, X) sample pairs show (1) Medicare audits have high error rates: more than 76% of these payments were considered to have been paid in error; and (2) the patterns in these samples support an “All-or-Nothing” mixture model for (Y, X) previously defined in the literature. Model-based Monte Carlo testing procedures for Medicare sampling plans are discussed, as well as stratification methods based on anticipated model moments. In terms of viability (achieving the 90% confidence level) a new stratification method defined here is competitive with the best of the many existing methods tested and seems less sensitive to choice of operating parameters. In terms of overpayment recovery (equivalent to precision) the new method is also comparable to the best of the many existing methods tested. Unfortunately, no stratification algorithm tested was ever viable for more than about half of the 104 test populations.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200006Description: Survey researchers are increasingly turning to multimode data collection to deal with declines in survey response rates and increasing costs. An efficient approach offers the less costly modes (e.g., web) followed with a more expensive mode for a subsample of the units (e.g., households) within each primary sampling unit (PSU). We present two alternatives to this traditional design. One alternative subsamples PSUs rather than units to constrain costs. The second is a hybrid design that includes a clustered (two-stage) sample and an independent, unclustered sample. Using a simulation, we demonstrate the hybrid design has considerable advantages.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200008Description: In this article, we use a slightly simplified version of the method by Fickus, Mixon and Poteet (2013) to define a flexible parameterization of the kernels of determinantal sampling designs with fixed first-order inclusion probabilities. For specific values of the multidimensional parameter, we get back to a matrix from the family PII from Loonis and Mary (2019). We speculate that, among the determinantal designs with fixed inclusion probabilities, the minimum variance of the Horvitz and Thompson estimator (1952) of a variable of interest is expressed relative to PII. We provide experimental R programs that facilitate the appropriation of various concepts presented in the article, some of which are described as non-trivial by Fickus et al. (2013). A longer version of this article, including proofs and a more detailed presentation of the determinantal designs, is also available.Release date: 2024-01-03
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Reference (29)
Reference (29) (20 to 30 of 29 results)
- 21. Calculation of change for annual business surveys ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015027Description:
The disseminated results of annual business surveys inevitably contain statistics that are changing. Since the economic sphere is increasingly dynamic, a simple difference of aggregates between n-l and n is no longer sufficient to provide an overall description of what has happened. The change calculation module in the new generation of annual business surveys divides overall change into various components (births, deaths, inter-industry migration) and calculates change on the basis of a constant field, assigning special importance to restructurings. The main difficulties lie in establishing subsamples, reweighting, calibrating according to calculable changes, and taking account of restructuring.
Release date: 1999-10-22 - Surveys and statistical programs – Documentation: 11-522-X19980015029Description:
In longitudinal surveys, sample subjects are observed over several time points. This feature typically leads to dependent observations on the same subject, in addition to the customary correlations across subjects induced by the sample design. Much research in the literature has focussed on modeling the marginal mean of a response as a function of covariates. Liang and Zeger (1986) used generalized estimating equations (GEE), requiring only correct specification of the marginal mean, and obtained standard errors of regression parameter estimates and associated Wald tests, assuming a "working" correlation structure for the repeated measurements on a sample subject. Rotnitzky and Jewell (1990) developed quasi-score tests and Rao-Scott adjustments to "working" quasi-score tests under marginal models. These methods are asymptotically robust to misspecification of the within-subject correlation structure, but assume independence of sample subjects which is not satisfied for complex longitudinal survey data based on stratified multi-stage sampling. We proposed asymptotically valid Wald and quasi-score tests for longitudinal survey data, using the Taylor Linearization and jackknife methods. Alternative tests, based on Rao-Scott adjustments to naive tests that ignore survey design features and on Bonferroni-t, are also developed. These tests are particularly useful when the effective degrees of freedom, usually taken as the total number of sample primary units (clusters) minus the number of strata, is small.
Release date: 1999-10-22 - 23. Estimating the incidence of dementia from longitudinal two-phase sampling with nonignorable missing data ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015030Description:
Two-phase sampling designs have been conducted in waves to estimate the incidence of a rare disease such as dementia. Estimation of disease incidence from longitudinal dementia study has to appropriately adjust for data missing by death as well as the sampling design used at each study wave. In this paper we adopt a selection model approach to model the missing data by death and use a likelihood approach to derive incidence estimates. A modified EM algorithm is used to deal with data missing by sampling selection. The non-paramedic jackknife variance estimator is used to derive variance estimates for the model parameters and the incidence estimates. The proposed approaches are applied to data from the Indianapolis-Ibadan Dementia Study.
Release date: 1999-10-22 - 24. Estimation with partial overlap longitudinal samples ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015035Description:
In a longitudinal survey conducted for k periods some units may be observed for less than k of the periods. Examples include, surveys designed with partially overlapping subsamples, a pure panel survey with nonresponse, and a panel survey supplemented with additional samples for some of the time periods. Estimators of the regression type are exhibited for such surveys. An application to special studies associated with the National Resources Inventory is discussed.
Release date: 1999-10-22 - Notices and consultations: 13F0026M1999001Description:
The main objectives of a new Canadian survey measuring asset and debt holding of families and individuals will be to update wealth information that is over one decade old; to improve the reliability of the wealth estimates; and, to provide a primary tool for analysing many important policy issues related to the distribution of assets and debts, future consumption possibilities, and savings behaviour that is of interest to governments, business and communities.
This paper is the document that launched the development of the new asset and debt survey, subsequently renamed the Survey of Financial Security. It looks at the conceptual framework for the survey, including the appropriate unit of measurement (family, household or person) and discusses measurement issues such as establishing an accounting framework for assets and debts. The variables proposed for inclusion are also identified. The paper poses several questions to readers and asks for comments and feedback.
Release date: 1999-03-23 - Notices and consultations: 13F0026M1999002Description:
This document summarizes the comments and feedback received on an earlier document: Towards a new Canadian asset and debt survey - A content discussion paper. The new asset and debt survey (now called the Survey of Financial Security) is to update the wealth information on Canadian families and unattached individuals. Since the last data collection was conducted in 1984, it was essential to include a consultative process in the development of the survey in order to obtain feedback on issues of concern and to define the conceptual framework for the survey.
Comments on the content discussion paper are summarized by major theme and sections indicate how the suggestions are being incorporated into the survey or why they could not be incorporated. This paper also mentions the main objectives of the survey and provides an overview of the survey content, revised according to the feedback from the discussion paper.
Release date: 1999-03-23 - 27. Proposal for an Asset and Debt Survey ArchivedSurveys and statistical programs – Documentation: 13F0026M1999003Description:
This paper presents a proposal for conducting a Canadian asset and debt survey. The first step in preparing this proposal was the release, in February 1997, of a document entitled Towards a new Canadian asset and debt survey whose intent was to elicit feedback on the initial thinking regarding the content of the survey.
This paper reviews the conceptual framework for a new asset and debt survey, data requirements, survey design, collection methodology and testing. It provides also an overview of the anticipated data processing system, describes the analysis and dissemination plan (analytical products and microdata files), and identifies the survey costs and major milestones. Finally, it presents the management/coordination approach used.
Release date: 1999-03-23 - Surveys and statistical programs – Documentation: 75F0002M1993019Description:
This paper examines the issues and the procedures designed to maintain a representative sample of the population for the Survey of Labour and Income Dynamics (SLID).
Release date: 1995-12-30 - Surveys and statistical programs – Documentation: 75F0002M1994001Description:
This paper describes the Survey of Labour and Income Dynamics (SLID) following rules, which govern who is traced and who is interviewed. It also outlines the conceptual basis for these procedures.
Release date: 1995-12-30