Frames and coverage

Filter results by

Search Help
Currently selected filters that can be removed

Keyword(s)

Geography

1 facets displayed. 0 facets selected.

Survey or statistical program

3 facets displayed. 0 facets selected.

Content

1 facets displayed. 0 facets selected.
Sort Help
entries

Results

All (64)

All (64) (40 to 50 of 64 results)

  • Surveys and statistical programs – Documentation: 12-001-X19980013906
    Description:

    In sample surveys, the units contained in the sampling frame ideally have a one-to-one correspondence with the elements in the target population under study. In many cases, however, the frame has a many-to-many structure. That is, a unit in the frame may be associated with multiple target population elements and a target population element may be associated with multiple frame units. Such was the case in a building characteristics survey in which the frame was a list of street addresses, but the target population was commercial buildings. The frame was messy because a street address corresponded either to a single building, multiple buildings, or part of a building. In this paper, we develop estimators and formulas for their variances in both simple and stratified random sampling designs when the frame has a many-to-many structure.

    Release date: 1998-07-31

  • Surveys and statistical programs – Documentation: 12-001-X19980013912
    Description:

    Efficient estimates of population size and totals based on information from multiple list frames and an independent area frame are considered. This work is an extension of the methodology proposed by Harley (1962) which considers two general frames. A main disadvantage of list frames is that they are typically incomplete. In this paper, we propose several methods to address frame deficiencies. A joint list-area sampling design incorporates multiple frames and achieves full coverage of the target population. For each combination of frames, we present the appropriate notation, likelihood function, and parameter estimators. Results from a simulation study that compares the various properties of the proposed estimators are also presented.

    Release date: 1998-07-31

  • Surveys and statistical programs – Documentation: 12-001-X19980013913
    Description:

    Temporary mobility is hypothesized to contribute toward within-household coverage error since it may affect an individual's determination of "usual residence" - a concept commonly applied when listing persons as part of a household-based survey or census. This paper explores a typology of temporary mobility patterns and how they relate to the identification of usual residence. Temporary mobility is defined by the pattern of movement away from, but usually back to a single residence over a two-three month reference period. The typology is constructed using two dimensions: the variety of places visited and the frequency of visits made. Using data from the U.S. Living Situation Survey (LSS) conducted in 1993, four types of temporary mobility patterns are identified. In particular, two groups exhibiting patterns of repeat visit behavior were found to contain more of the types of people who tend to be missed during censuses and surveys. Log-linear modeling indicates spent away and demographic characteristics.

    Release date: 1998-07-31

  • Articles and reports: 91F0015M1998005
    Geography: Canada
    Description:

    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

  • Surveys and statistical programs – Documentation: 12-001-X19970023620
    Description:

    Since France has no population registers, population censuses are the basis for its socio-demographic information system. However, between two censuses, some data must be updated, in particular at a high level of geographic detail, especially since censuses are tending, for various reasons, to be less frequent. In 1993, the Institut National de la Statistique et des Études Économiques (INSEE) set up a team whose objective was to propose a system to substantially improve the existing mechanism for making small area population estimates. Its task was twofold: to prepare an efficient and robust synthesis of the information available from different administrative sources, and to assemble a sufficient number of "good" sources. The "multi-source" system that it designed, which is reported on here, is flexible and reliable, without being overly complex.

    Release date: 1998-03-12

  • Articles and reports: 12-001-X199500214391
    Description:

    Statistical process control can be used as a quality tool to assure the accuracy of sampling frames that are constructed periodically. Sampling frame sizes are plotted in a control chart to detect special causes of variation. Procedures to identify the appropriate time series (ARIMA) model for serially correlated observations are described. Applications of time series analysis to the construction of control charts are discussed. Data from the United States Department of Labor’s Unemployment Insurance Benefits Quality Control Program is used to illustrate the technique.

    Release date: 1995-12-15

  • Articles and reports: 12-001-X199500214393
    Description:

    Major uncertainties about the quality of elderly population and death enumerations in the United States result from coverage and content errors in the censuses and the death registration system. This study evaluates the consistency of reported data between the two sources for the white and the African-American populations. The focus is on the older population (aged 60 and above), where mortality trends have the greatest impact on social programs and where data are most problematic. Using intercensal cohort analysis, age-specific inconsistencies between the sources are identified for two periods: 1970-1980 and 1980-1990. The U.S. data inconsistencies are examined in light of evidence in the literature regarding the nature of coverage and content errors in the data sources. Data for African-Americans are highly inconsistent in the 1970-1990 period, likely the result of age overstatement in censuses relative to death registration. Inconsistencies also exist for whites in the 1970-1980 intercensal period. We argue that the primary source of this error is an undercount in the 1970 census relative to both the 1980 census and the death registration. In contrast, the 1980-1990 data for whites, and particularly for white females, are highly consistent, far better than in most European countries.

    Release date: 1995-12-15

  • Articles and reports: 12-001-X199500114410
    Description:

    As part of the decision on adjustment of the 1990 Decennial Census, the U.S. Census Bureau investigated possible heterogeneity of undercount rates between parts of different states falling in the same adjustment cell or poststratum. Five “surrogate variables” believed to be associated with undercount were analyzed using a large extract from the census and significant heterogeneity was found. Analysis of Post Enumeration Survey on undercount rates showed that more variance was explained by poststratification variables than by state, supporting the decision to use the poststratum as the adjustment cell. Significant interstate heterogeneity was found in 19 out of 99 poststratum groups (mainly in nonurban areas), but there was little if any evidence that the poststratified estimator was biased against particular states after aggregating across poststrata. Nonetheless, this issue should be addressed in future coverage evaluation studies.

    Release date: 1995-06-15

  • Articles and reports: 12-001-X199500114411
    Description:

    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-X199400214422
    Description:

    Dual system estimation (DSE) has been used since 1950 by the U.S. Bureau of Census for coverage evaluation of the decennial census. In the DSE approach, data from a sample is combined with data from the census to estimate census undercount and overcount. DSE relies upon the assumption that individuals in both the census and the sample can be matched perfectly. The unavoidable mismatches and erroneous nonmatches reduce the accuracy of the DSE. This paper reconsiders the DSE approach by relaxing the perfect matching assumption and proposes models to describe two types of matching errors, false matches of nonmatching cases and false nonmatches of matching cases. Methods for estimating population total and census undercount are presented and illustrated using data from 1986 Los Angeles test census and 1990 Decennial Census.

    Release date: 1994-12-15
Data (0)

Data (0) (0 results)

No content available at this time.

Analysis (51)

Analysis (51) (0 to 10 of 51 results)

  • Stats in brief: 11-629-X2019004
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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

  • Articles and reports: 11-522-X20050019449
    Description:

    Literature about Multiple Frame estimation theory mainly concentrates over the Dual Frame case and it is only rarely concerned with the important practical issue of the variance estimation. By using a multiplicity approach a fixed weights Single Frame estimator for Multiple Frame Survey is proposed.

    Release date: 2007-03-02
Reference (18)

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

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

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
    Description:

    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
Date modified: