Survey design
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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) (50 to 60 of 301 results)
- Articles and reports: 89-648-X2016001Description:
Linkages between survey and administrative data are an increasingly common practice, due in part to the reduced burden to respondents, and to the data that can be obtained at a relatively low cost. Historical linkage, or the linkage of administrative data from previous years to the year of the survey, compounds these benefits by providing additional years of data. This paper examines the Longitudinal and International Study of Adults (LISA), which was linked to historical tax data on personal income tax returns (T1) and those collected from employers’ files (T4), among others not mentioned in this paper. It presents trends in historical linkage rates, compares the coherence of administrative data between the T1 and T4, presents the ability to use the data to create balanced panels, and uses the T1 data to produce age-earnings profiles by sex. The results show that the historical linkage rate is high (over 90% in most cases) and stable over time for respondents who are likely to file a tax return, and that the T1 and T4 administrative sources show similar earnings. Moreover, long balanced panels of up to 30 years in length (at the time of writing) can be created using LISA administrative linkage data.
Release date: 2016-08-18 - 52. A Bayesian analysis of survey design parameters ArchivedArticles and reports: 11-522-X201700014745Description:
In the design of surveys a number of parameters like contact propensities, participation propensities and costs per sample unit play a decisive role. In on-going surveys, these survey design parameters are usually estimated from previous experience and updated gradually with new experience. In new surveys, these parameters are estimated from expert opinion and experience with similar surveys. Although survey institutes have a fair expertise and experience, the postulation, estimation and updating of survey design parameters is rarely done in a systematic way. This paper presents a Bayesian framework to include and update prior knowledge and expert opinion about the parameters. This framework is set in the context of adaptive survey designs in which different population units may receive different treatment given quality and cost objectives. For this type of survey, the accuracy of design parameters becomes even more crucial to effective design decisions. The framework allows for a Bayesian analysis of the performance of a survey during data collection and in between waves of a survey. We demonstrate the Bayesian analysis using a realistic simulation study.
Release date: 2016-03-24 - 53. Domain sample allocation within primary sampling units in designing domain-level equal probability selection methods ArchivedArticles and reports: 12-001-X201500214229Description:
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.
Release date: 2015-12-17 - Articles and reports: 12-001-X201500214230Description:
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.
Release date: 2015-12-17 - 55. Optimum allocation for a dual-frame telephone survey ArchivedArticles and reports: 12-001-X201500214237Description:
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.
Release date: 2015-12-17 - Articles and reports: 12-001-X201500214249Description:
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).
Release date: 2015-12-17 - Articles and reports: 12-001-X201400214090Description:
When studying a finite population, it is sometimes necessary to select samples from several sampling frames in order to represent all individuals. Here we are interested in the scenario where two samples are selected using a two-stage design, with common first-stage selection. We apply the Hartley (1962), Bankier (1986) and Kalton and Anderson (1986) methods, and we show that these methods can be applied conditional on first-stage selection. We also compare the performance of several estimators as part of a simulation study. Our results suggest that the estimator should be chosen carefully when there are multiple sampling frames, and that a simple estimator is sometimes preferable, even if it uses only part of the information collected.
Release date: 2014-12-19 - 58. Fractional hot deck imputation for robust inference under item nonresponse in survey sampling ArchivedArticles and reports: 12-001-X201400214091Description: Parametric fractional imputation (PFI), proposed by Kim (2011), is a tool for general purpose parameter estimation under missing data. We propose a fractional hot deck imputation (FHDI) which is more robust than PFI or multiple imputation. In the proposed method, the imputed values are chosen from the set of respondents and assigned proper fractional weights. The weights are then adjusted to meet certain calibration conditions, which makes the resulting FHDI estimator efficient. Two simulation studies are presented to compare the proposed method with existing methods.Release date: 2014-12-19
- 59. Chi-squared tests in dual frame surveys ArchivedArticles and reports: 12-001-X201400214096Description:
In order to obtain better coverage of the population of interest and cost less, a number of surveys employ dual frame structure, in which independent samples are taken from two overlapping sampling frames. This research considers chi-squared tests in dual frame surveys when categorical data is encountered. We extend generalized Wald’s test (Wald 1943), Rao-Scott first-order and second-order corrected tests (Rao and Scott 1981) from a single survey to a dual frame survey and derive the asymptotic distributions. Simulation studies show that both Rao-Scott type corrected tests work well and thus are recommended for use in dual frame surveys. An example is given to illustrate the usage of the developed tests.
Release date: 2014-12-19 - Articles and reports: 12-001-X201400214119Description:
When considering sample stratification by several variables, we often face the case where the expected number of sample units to be selected in each stratum is very small and the total number of units to be selected is smaller than the total number of strata. These stratified sample designs are specifically represented by the tabular arrays with real numbers, called controlled selection problems, and are beyond the reach of conventional methods of allocation. Many algorithms for solving these problems have been studied over about 60 years beginning with Goodman and Kish (1950). Those developed more recently are especially computer intensive and always find the solutions. However, there still remains the unanswered question: In what sense are the solutions to a controlled selection problem obtained from those algorithms optimal? We introduce the general concept of optimal solutions, and propose a new controlled selection algorithm based on typical distance functions to achieve solutions. This algorithm can be easily performed by a new SAS-based software. This study focuses on two-way stratification designs. The controlled selection solutions from the new algorithm are compared with those from existing algorithms using several examples. The new algorithm successfully obtains robust solutions to two-way controlled selection problems that meet the optimality criteria.
Release date: 2014-12-19
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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