Frames and coverage

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  • Articles and reports: 12-001-X20020026431

    When stand-alone sampling frames that list all establishments and their measures of size are available, establishment surveys typically use the Hansen-Hurwitz (HH) PPS (probability proportional to size) estimator to estimate the volume of transactions that establishments have with populations. This paper proposes the network sampling (NS) version of the HH estimator as a potential competitor of the PPS estimator. The NS estimator depends on the population survey-generated establishment frame that lists households and their selection probabilities in a population sample survey, and the number of transactions, if any, of each household with each establishment. A statistical model is developed in this paper to compare the efficiencies of the HH and NS estimators in single-stage and two-stage establishment sample surveys assuming the stand-alone sampling frame and the population survey-generated frame are flawless in coverage and size measures.

    Release date: 2003-01-29

  • Articles and reports: 11-522-X20010016248

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The Sawmill Survey is a voluntary census of sawmills in Great Britain. It is limited to fixed mills using domestically-grown timber. Three approaches to assess the coverage of this survey are described:

    (1) A sample survey of the sawmilling industry from the UK's business register, excluding businesses already sampled in the Sawmill Survey, is used to assess the undercoverage in the list of known sawmills; (2) A non-response follow-up using local knowledge of regional officers of the Forestry Commission, is used to estimate the sawmills that do not respond (mostly the smaller mills); and (3) A survey of small-scale sawmills and mobile sawmills (many of these businesses are micro-enterprises) is conducted to analyse their significance.

    These three approaches are synthesized to give an estimate of the coverage of the original survey compared with the total activity identified, and to estimate the importance of micro-enterprises to the sawmilling industry in Great Britain.

    Release date: 2002-09-12

  • Articles and reports: 11-522-X20010016266

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The key measure of Census quality is the level of response achieved. In recent censuses around the world, this level has been in the high nineties percentage range. This was also true of the 1991 Census in Britain (98%). However, what was particularly noticeable about this Census was the differential response rate and the difficulty in effectively measuring this rate. The United Kingdom set up the One Number Census program in order to research and develop a more effective methodology to measure and account for under-enumeration in the 2001 Census. The key element in this process is the Census Coverage Survey - a significantly larger and redesigned post-enumeration survey.

    This paper describes the planning and design of the Census Coverage Survey with particular emphasis on the implementation of the proposed field methodology. It also provides a high-level overview of the success of this survey.

    Release date: 2002-09-12

  • Articles and reports: 11-522-X20010016296

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The Canadian Labour Force Survey (LFS) is one of Statistics Canada's most important surveys. It is a monthly survey that collects data concerning the person's labour force status, the nature of the person's work or reason for not working, and the person's demographics. The survey sample consists of approximately 52,000 households. Coverage error is a measure of data quality that is important to any survey. One of the key measures of coverage error in the LFS is the percentage difference between the Census of Population estimates and the LFS population counts; this error is called slippage. A negative value indicates that the LFS has a problem of overcoverage, while a positive value indicates the LFS has an undercoverage problem. In general, slippage is positive, thus meaning that the LFS consistently misses people who should be enumerated.

    The purpose of this study was to determine why slippage is increasing and what can be done to remedy it. The study was conducted in two stages. The first stage was a historical review of the projects that have studied and tried to control slippage in the LFS, as well as the operational changes that have been implemented over time. The second stage was an analysis of factors such as vacancy rates, non-response, demographics, urban and rural status and the impact of these factors on the slippage rate.

    Release date: 2002-09-12

  • Articles and reports: 12-001-X20020016419

    Since some individuals in a population may lack telephones, telephone surveys using random digit dialling within strata may result in asymptotically biased estimators of ratios. The impact from not being able to sample the non-telephone population is examined. We take into account the propensity that a household owns a telephone, when proposing a post-stratified telephone-weighted estimator, which seems to perform better than the typical post-stratified estimator in terms of mean squared error. Such coverage propensities are estimated using the Public Use Microdata Samples, as provided by the United States Census. Non-post-stratified estimators are considered when sample sizes are small. The asymptotic mean squared error, along with its estimate based on a sample of each of the estimators is derived. Real examples are analysed using the Public Use Microdata Samples. Other forms of no-nresponse are not examined herein.

    Release date: 2002-07-05

  • Articles and reports: 12-001-X20010026089

    Telephone surveys are a convenient and efficient method of data collection. Bias may be introduced into population estimates, however, by the exclusion of nontelephone households from these surveys. Data from the U.S. Federal Communications Commission (FCC) indicates that five and a half to six percent of American households are without phone service at any given time. The bias introduced can be significant since nontelephone households may differ from telephone households in ways that are not adequately handled by poststratification. Many households, called "transients", move in and out of the telephone population during the year, sometimes due to economic reasons or relocation. The transient telephone population may be representative of the nontelephone population in general since its members have recently been in the nontelephone population.

    Release date: 2002-02-28

  • Articles and reports: 12-001-X20000025531

    Information from list and area sampling frames is combined to obtain efficient estimates of population size and totals. We consider the case where the probabilities of inclusion on the list frames are heterogeneous and are modeled as a function of covariates. We adapt and modify the methodology of Huggins (1989) and Albo (1990) for modeling auxiliary variables in capture-recapture studies using a logistic regression model. We present the results from a simulation study which compares various estimators of frame size and population totals using the logistic regression approach to modeling heterogeneous inclusion probabilities.

    Release date: 2001-02-28

  • Surveys and statistical programs – Documentation: 12-001-X20000015177

    The 1996 Canadian Census is adjusted for coverage error as estimated primarily through the Reverse Record Check (RRC). In this paper, we will show how there is a wealth of additional information from the 1996 Reverse Record Check of direct value to population estimation. Beyond its ability to estimate coverage error, it is possible to extend the Reverse Record Check classification results to obtain an alternative estimate of demographic growth - potentially decomposed by component. This added feature of the Reverse Record Check provides promise in the evaluation of estimated census coverage error as well as insight as to possible problems in the estimation of selected components in the population estimates program.

    Release date: 2000-08-30

  • Surveys and statistical programs – Documentation: 92-370-X

    Series description

    This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and the Technical Reports - as well as geography reference products - GeoSuite and Reference Maps.

    Product description

    Technical Reports examine the quality of data from the 1996 Census, a large and complex undertaking. While considerable effort was taken to ensure high quality standards throughout each step, the results are subject to a certain degree of error. Each report looks at the collection and processing operations and presents results from data evaluation, as well as notes on historical comparability.

    Technical Reports are aimed at moderate and sophisticated users but are written in a manner which could make them useful to all census data users. Most of the technical reports have been cancelled, with the exception of Age, Sex, Marital Status and Common-law Status, Coverage and Sampling and Weighting. These reports will be available as bilingual publications as well as being available in both official languages on the Internet as free products.

    This report deals with coverage errors, which occured when persons, households, dwellings or families were missed by the 1996 Census or enumerated in error. Coverage errors are one of the most important types of error since they affect not only the accuracy of the counts of the various census universes but also the accuracy of all of the census data describing the characteristics of these universes. With this information, users can determine the risks involved in basing conclusions or decisions on census data.

    Release date: 1999-12-14

  • Surveys and statistical programs – Documentation: 12-001-X19980024353

    This paper studies response errors in the Current Population Survey of the U.S. Bureau of the Census and assesses their impact on the unemployment rates published by the Bureau of Labour Statistics. The measurement of these error rates is obtained from reinterview data, using an extension of the Hui and Walter (1980) procedure for the evaluation of diagnostic tests. Unlike prior studies which assumed that the reconciled reinterview yields the true status, the method estimates the error rates in both interviews. Using these estimated error rates, we show that the misclassification in the original survey creates a cyclical effect on the reported estimated unemployment rates. In particular, the degress of underestimation increases when true unemployment is high. As there was insufficient data to distinguish between a model assuming that the misclassification rates are the same throughout the business cycle, and one that allows the error rates to differ in periods of low, moderate and high unemployment, our findings should be regarded as preliminary. Nonetheless, they indicated that the relationship between the models used to assess the accuracy of diagnostic tests, and those measuring misclassification rates of survey data, deserves further study.

    Release date: 1999-01-14
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  • Articles and reports: 12-001-X201900300008

    Dual frame surveys are useful when no single frame with adequate coverage exists. However estimators from dual frame designs require knowledge of the frame memberships of each sampled unit. When this information is not available from the frame itself, it is often collected from the respondent. When respondents provide incorrect membership information, the resulting estimators of means or totals can be biased. A method for reducing this bias, using accurate membership information obtained about a subsample of respondents, is proposed. The properties of the new estimator are examined and compared to alternative estimators. The proposed estimator is applied to the data from the motivating example, which was a recreational angler survey, using an address frame and an incomplete fishing license frame.

    Release date: 2019-12-17

  • Stats in brief: 11-629-X2019004

    This video explains the Necessity and Proportionality Framework, which assesses data sensitivity and gathering in a more integrated way while ensuring the data needs of Canadians are met.

    Release date: 2019-11-26

  • Stats in brief: 11-629-X2016003

    Discover how the Enterprise Portfolio Management team (EPM) supports some of Canada’s largest enterprises.

    Release date: 2016-06-02

  • Articles and reports: 12-001-X201500114149

    This paper introduces a general framework for deriving the optimal inclusion probabilities for a variety of survey contexts in which disseminating survey estimates of pre-established accuracy for a multiplicity of both variables and domains of interest is required. The framework can define either standard stratified or incomplete stratified sampling designs. The optimal inclusion probabilities are obtained by minimizing costs through an algorithm that guarantees the bounding of sampling errors at the domains level, assuming that the domain membership variables are available in the sampling frame. The target variables are unknown, but can be predicted with suitable super-population models. The algorithm takes properly into account this model uncertainty. Some experiments based on real data show the empirical properties of the algorithm.

    Release date: 2015-06-29

  • Articles and reports: 12-001-X201400214128

    Users, funders and providers of official statistics want estimates that are “wider, deeper, quicker, better, cheaper” (channeling Tim Holt, former head of the UK Office for National Statistics), to which I would add “more relevant” and “less burdensome”. Since World War II, we have relied heavily on the probability sample survey as the best we could do - and that best being very good - to meet these goals for estimates of household income and unemployment, self-reported health status, time use, crime victimization, business activity, commodity flows, consumer and business expenditures, et al. Faced with secularly declining unit and item response rates and evidence of reporting error, we have responded in many ways, including the use of multiple survey modes, more sophisticated weighting and imputation methods, adaptive design, cognitive testing of survey items, and other means to maintain data quality. For statistics on the business sector, in order to reduce burden and costs, we long ago moved away from relying solely on surveys to produce needed estimates, but, to date, we have not done that for household surveys, at least not in the United States. I argue that we can and must move from a paradigm of producing the best estimates possible from a survey to that of producing the best possible estimates to meet user needs from multiple data sources. Such sources include administrative records and, increasingly, transaction and Internet-based data. I provide two examples - household income and plumbing facilities - to illustrate my thesis. I suggest ways to inculcate a culture of official statistics that focuses on the end result of relevant, timely, accurate and cost-effective statistics and treats surveys, along with other data sources, as means to that end.

    Release date: 2014-12-19

  • Articles and reports: 12-001-X201100111443

    Dual frame telephone surveys are becoming common in the U.S. because of the incompleteness of the landline frame as people transition to cell phones. This article examines nonsampling errors in dual frame telephone surveys. Even though nonsampling errors are ignored in much of the dual frame literature, we find that under some conditions substantial biases may arise in dual frame telephone surveys due to these errors. We specifically explore biases due to nonresponse and measurement error in these telephone surveys. To reduce the bias resulting from these errors, we propose dual frame sampling and weighting methods. The compositing factor for combining the estimates from the two frames is shown to play an important role in reducing nonresponse bias.

    Release date: 2011-06-29

  • Articles and reports: 11-522-X200800010972

    Background: Evaluation of the coverage that results from linking routinely collected administrative hospital data with survey data is an important preliminary step to undertaking analyses based on the linked file. Data and methods: To evaluate the coverage of the linkage between data from cycle 1.1 of the Canadian Community Health Survey (CCHS) and in-patient hospital data (Health Person-Oriented Information or HPOI), the number of people admitted to hospital according to HPOI was compared with the weighted estimate for CCHS respondents who were successfully linked to HPOI. Differences between HPOI and the linked and weighted CCHS estimate indicated linkage failure and/or undercoverage. Results: According to HPOI, from September 2000 through November 2001, 1,572,343 people (outside Quebec) aged 12 or older were hospitalized. Weighted estimates from the linked CCHS, adjusted for agreement to link and plausible health number, were 7.7% lower. Coverage rates were similar for males and females. Provincial rates did not differ from those for the rest of Canada, although differences were apparent for the territories. Coverage rates were significantly lower among people aged 75 or older than among those aged 12 to 74.

    Release date: 2009-12-03

  • Articles and reports: 11-522-X200800010979

    Prior to 2006, the Canadian Census of Population relied on field staff to deliver questionnaires to all dwellings in Canada. For the 2006 Census, an address frame was created to cover almost 70% of dwellings in Canada, and these questionnaires were delivered by Canada Post. For the 2011 Census, Statistics Canada aims to expand this frame further, with a target of delivering questionnaires by mail to between 80% and 85% of dwellings. Mailing questionnaires for the Census raises a number of issues, among them: ensuring returned questionnaires are counted in the right area, creating an up to date address frame that includes all new growth, and determining which areas are unsuitable for having questionnaires delivered by mail. Changes to the address frame update procedures for 2011, most notably the decision to use purely administrative data as the frame wherever possible and conduct field update exercises only where deemed necessary, provide a new set of challenges for the 2011 Census.

    Release date: 2009-12-03

  • Articles and reports: 11-522-X200600110420

    Most major survey research organizations in the United States and Canada do not include wireless telephone numbers when conducting random-digit-dialed (RDD) household telephone surveys. In this paper, we offer the most up-to-date estimates available from the U.S. National Center for Health Statistics and Statistics Canada concerning the prevalence and demographic characteristics of the wireless-only population. We then present data from the U.S. National Health Interview Survey on the health and health care access of wireless-only adults, and we examine the potential for coverage bias when health research is conducted using RDD surveys that exclude wireless telephone numbers.

    Release date: 2008-03-17

  • Articles and reports: 12-001-X200700210497

    Coverage deficiencies are estimated and analysed for the 2000 population census in Switzerland. For the undercoverage component, the estimation is based on a sample independent of the census and a match with the census. For the overcoverage component, the estimation is based on a sample drawn from the census list and a match with the rest of the census. The over- and undercoverage components are then combined to obtain an estimate of the resulting net coverage. This estimate is based on a capture-recapture model, named the dual system, combined with a synthetic model. The estimators are calculated for the full population and different subgroups, with a variance estimated by a stratified jackknife. The coverage analyses are supplemented by a study of matches between the independent sample and the census in order to determine potential errors of measurement and location in the census data.

    Release date: 2008-01-03
Reference (18)

Reference (18) (0 to 10 of 18 results)

  • Surveys and statistical programs – Documentation: 98-303-X

    The Coverage Technical Report will present the error included in census data that results from either persons being missed (not enumerated) or from persons being enumerated more than once by the 2016 Census. The population coverage error is one of the most important types of errors because it affects not only the accuracy of population counts, but also the accuracy of all the census data results describing the characteristics of the population universe.

    Release date: 2019-11-13

  • Surveys and statistical programs – Documentation: 11-522-X201700014708

    Statistics Canada’s Household Survey Frames (HSF) Programme provides various universe files that can be used alone or in combination to improve survey design, sampling, collection, and processing in the traditional “need to contact a household model.” Even as surveys are migrating onto these core suite of products, the HSF is starting to plan the changes to infrastructure, organisation, and linkages with other data assets in Statistics Canada that will help enable a shift to increased use of a wide variety of administrative data as input to the social statistics programme. The presentation will provide an overview of the HSF Programme, foundational concepts that will need to be implemented to expand linkage potential, and will identify strategic research being under-taken toward 2021.

    Release date: 2016-03-24

  • Surveys and statistical programs – Documentation: 11-522-X201300014269

    The Census Overcoverage Study (COS) is a critical post-census coverage measurement study. Its main objective is to produce estimates of the number of people erroneously enumerated, by province and territory, study the characteristics of individuals counted multiple times and identify possible reasons for the errors. The COS is based on the sampling and clerical review of groups of connected records that are built by linking the census response database to an administrative frame, and to itself. In this paper we describe the new 2011 COS methodology. This methodology has incorporated numerous improvements including a greater use of probabilistic record-linkage, the estimation of linking parameters with an Expectation-Maximization (E-M) algorithm, and the efficient use of household information to detect more overcoverage cases.

    Release date: 2014-10-31

  • Surveys and statistical programs – Documentation: 12-001-X201100211608

    Designs and estimators for the single frame surveys currently used by U.S. government agencies were developed in response to practical problems. Federal household surveys now face challenges of decreasing response rates and frame coverage, higher data collection costs, and increasing demand for small area statistics. Multiple frame surveys, in which independent samples are drawn from separate frames, can be used to help meet some of these challenges. Examples include combining a list frame with an area frame or using two frames to sample landline telephone households and cellular telephone households. We review point estimators and weight adjustments that can be used to analyze multiple frame surveys with standard survey software, and summarize construction of replicate weights for variance estimation. Because of their increased complexity, multiple frame surveys face some challenges not found in single frame surveys. We investigate misclassification bias in multiple frame surveys, and propose a method for correcting for this bias when misclassification probabilities are known. Finally, we discuss research that is needed on nonsampling errors with multiple frame surveys.

    Release date: 2011-12-21

  • Surveys and statistical programs – Documentation: 87-542-X2011001
    Geography: Canada

    The first issue of the series presents the Conceptual Framework for Culture Statistics 2011, a revision of the 2004 Canadian Framework for Culture Statistics.

    The conceptual framework contains an official statistical definition of culture and describes a set of culture domains that can be used to measure culture from creation to use.

    Release date: 2011-10-24

  • Surveys and statistical programs – Documentation: 87-542-X2011002
    Geography: Canada

    The second issue of this series is a companion piece to the Conceptual Framework for Culture Statistics 2011, a revision to the 2004 Canadian Framework for Culture Statistics.

    The guide maps the 2011 Canadian framework for culture statistics to the following Statistics Canada's standard classification systems: the North American Industry Classification System (NAICS) 2007, the North American Product Classification System (NAPCS) - Canada (Provisional Version 0.1), National Occupational Classification - Statistics (NOC-S) 2006 and Classification of Instructional Programs (CIP), Canada, 2000.

    It contains explanations, definitions and examples of how the classification codes are mapped to the conceptual framework. It also contains a series of tables that contain codes, by classification system, which help illustrate the framework domains and sub-domains, and flags those codes that do not map well to the framework.

    Release date: 2011-10-24

  • Surveys and statistical programs – Documentation: 87-542-X
    Geography: Canada

    This series the Canadian Framework for Culture Statistics 2011 replaces the 2004 Canadian Framework for Culture Statistics (Catalogue 81-595-MIE2004021).

    The first issue of this series presents the conceptual framework, including a definition of culture, domains and sub-domains, and criteria for their inclusion in culture. The second issue is a guide that maps the conceptual framework to selected standard classification systems. It is intended to foster a standard approach to the measurement of culture in Canada.

    Release date: 2011-10-24

  • Surveys and statistical programs – Documentation: 92-567-X

    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: 12-001-X200700210492

    Multiple Frame Surveys were originally proposed to foster cost savings on the basis of an optimality approach. As surveys on special, rare and difficult-to-sample populations are becoming more prominent, a single list of population units to be used as a sampling frame is often unavailable in sampling practice. In recent literature multiple frame designs have been put forward in order to increase population coverage, to improve response rates and to capture differences and subgroups. Alternative approaches to multiple frame estimation have appeared, all of them relying upon the virtual partition of the set of the available overlapping frames into disjointed domains. Hence the correct classification of sampled units into the domains is required for practical applications. In this paper a multiple frame estimator is proposed using a multiplicity approach. Multiplicity estimators require less information about unit domain membership hence they are insensitive to misclassification. Moreover the proposed estimator is analytically simple so that it is easy to implement and its exact variance is given. Empirical results from an extensive simulation study comparing the multiplicity estimator with major competitors are also provided.

    Release date: 2008-01-03

  • Surveys and statistical programs – Documentation: 92-394-X

    This report deals with coverage errors that occur when persons, households, dwellings or families are missed or enumerated in error by the census. After the 2001 Census was taken, a number of studies were carried out to estimate gross undercoverage, gross overcoverage and net undercoverage. This report presents the results of the Dwelling Classification Study, the Reverse Record Check Study, the Automated Match Study and the Collective Dwelling Study. The report first describes census universes, coverage error and census collection and processing procedures that may result in coverage error. Then it gives estimates of net undercoverage for a number of demographic characteristics. After, the technical report presents the methodology and results of each coverage study and the estimates of coverage error after describing how the results of the various studies are combined. A historical perspective completes the product.

    Release date: 2004-11-25
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