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  • Articles and reports: 12-001-X201100211605
    Description:

    Composite imputation is often used in business surveys. The term "composite" means that more than a single imputation method is used to impute missing values for a variable of interest. The literature on variance estimation in the presence of composite imputation is rather limited. To deal with this problem, we consider an extension of the methodology developed by Särndal (1992). Our extension is quite general and easy to implement provided that linear imputation methods are used to fill in the missing values. This class of imputation methods contains linear regression imputation, donor imputation and auxiliary value imputation, sometimes called cold-deck or substitution imputation. It thus covers the most common methods used by national statistical agencies for the imputation of missing values. Our methodology has been implemented in the System for the Estimation of Variance due to Nonresponse and Imputation (SEVANI) developed at Statistics Canada. Its performance is evaluated in a simulation study.

    Release date: 2011-12-21

  • Surveys and statistical programs – Documentation: 12-001-X201100211607
    Description:

    This paper describes recent developments in adaptive sampling strategies and introduces new variations on those strategies. Recent developments described included targeted random walk designs and adaptive web sampling. These designs are particularly suited for sampling in networks; for example, for finding a sample of people from a hidden human population by following social links from sample individuals to find additional members of the hidden population to add to the sample. Each of these designs can also be translated into spatial settings to produce flexible new spatial adaptive strategies for sampling unevenly distributed populations. Variations on these sampling strategies include versions in which the network or spatial links have unequal weights and are followed with unequal probabilities.

    Release date: 2011-12-21

  • Articles and reports: 12-001-X201100211609
    Description:

    This paper presents a review and assessment of the use of balanced sampling by means of the cube method. After defining the notion of balanced sample and balanced sampling, a short history of the concept of balancing is presented. The theory of the cube method is briefly presented. Emphasis is placed on the practical problems posed by balanced sampling: the interest of the method with respect to other sampling methods and calibration, the field of application, the accuracy of balancing, the choice of auxiliary variables and ways to implement the method.

    Release date: 2011-12-21

  • Articles and reports: 12-001-X201100211610
    Description:

    In this paper, a discussion of the three papers from the US Census Bureau special compilation is presented.

    Release date: 2011-12-21

  • Articles and reports: 65-507-M2011011
    Description:

    This issue presents statistics, derived from the Importer Register Database, on importing establishments for the years 2002 to 2009. This Importer Register Database provides importer statistics such as the number of importers and the value of their imports by industry, importer size, origin and province of residence.

    The establishment is the statistical unit of measure. Consequently, any reference made here to "importers" represents "statistical establishments that imported." Inclusion in the database requires that an establishment has imported merchandise in at least one year from 2002 to 2009. If an establishment does not import in a given year, that establishment is not included in the Register for that year.

    This report is divided into four sections: "Highlights" consist of an overview of results of the 2009 Importer Register Database; "Findings" contains more detailed analyses of the Importer Register Database; "Methodology, Data concepts and definitions" outlines the estimation methods and limitations as well as the fundamental principles of the Importer Register Database; and "Data tables" contain tabular data for the years from 2002 to 2009.

    Release date: 2011-12-06

  • Articles and reports: 65-507-M2010010
    Geography: Province or territory
    Description:

    This issue presents exporter statistics from 1996 to 2009 including the number of exporters, the value of their domestic exports by industry, exporter size, destination and province of residence as well as employment statistics of exporting establishments for the year 2009. The data in this issue are at the establishment level and are derived from the Exporter Register Database.

    Release date: 2011-10-28

  • 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: 12-001-X201100111444
    Description:

    Data linkage is the act of bringing together records that are believed to belong to the same unit (e.g., person or business) from two or more files. It is a very common way to enhance dimensions such as time and breadth or depth of detail. Data linkage is often not an error-free process and can lead to linking a pair of records that do not belong to the same unit. There is an explosion of record linkage applications, yet there has been little work on assuring the quality of analyses using such linked files. Naively treating such a linked file as if it were linked without errors will, in general, lead to biased estimates. This paper develops a maximum likelihood estimator for contingency tables and logistic regression with incorrectly linked records. The estimation technique is simple and is implemented using the well-known EM algorithm. A well known method of linking records in the present context is probabilistic data linking. The paper demonstrates the effectiveness of the proposed estimators in an empirical study which uses probabilistic data linkage.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201100111445
    Description:

    In this paper we study small area estimation using area level models. We first consider the Fay-Herriot model (Fay and Herriot 1979) for the case of smoothed known sampling variances and the You-Chapman model (You and Chapman 2006) for the case of sampling variance modeling. Then we consider hierarchical Bayes (HB) spatial models that extend the Fay-Herriot and You-Chapman models by capturing both the geographically unstructured heterogeneity and spatial correlation effects among areas for local smoothing. The proposed models are implemented using the Gibbs sampling method for fully Bayesian inference. We apply the proposed models to the analysis of health survey data and make comparisons among the HB model-based estimates and direct design-based estimates. Our results have shown that the HB model-based estimates perform much better than the direct estimates. In addition, the proposed area level spatial models achieve smaller CVs than the Fay-Herriot and You-Chapman models, particularly for the areas with three or more neighbouring areas. Bayesian model comparison and model fit analysis are also presented.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201100111446
    Description:

    Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory performance of the method.

    Release date: 2011-06-29
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Analysis (16)

Analysis (16) (0 to 10 of 16 results)

  • Articles and reports: 12-001-X201100211605
    Description:

    Composite imputation is often used in business surveys. The term "composite" means that more than a single imputation method is used to impute missing values for a variable of interest. The literature on variance estimation in the presence of composite imputation is rather limited. To deal with this problem, we consider an extension of the methodology developed by Särndal (1992). Our extension is quite general and easy to implement provided that linear imputation methods are used to fill in the missing values. This class of imputation methods contains linear regression imputation, donor imputation and auxiliary value imputation, sometimes called cold-deck or substitution imputation. It thus covers the most common methods used by national statistical agencies for the imputation of missing values. Our methodology has been implemented in the System for the Estimation of Variance due to Nonresponse and Imputation (SEVANI) developed at Statistics Canada. Its performance is evaluated in a simulation study.

    Release date: 2011-12-21

  • Articles and reports: 12-001-X201100211609
    Description:

    This paper presents a review and assessment of the use of balanced sampling by means of the cube method. After defining the notion of balanced sample and balanced sampling, a short history of the concept of balancing is presented. The theory of the cube method is briefly presented. Emphasis is placed on the practical problems posed by balanced sampling: the interest of the method with respect to other sampling methods and calibration, the field of application, the accuracy of balancing, the choice of auxiliary variables and ways to implement the method.

    Release date: 2011-12-21

  • Articles and reports: 12-001-X201100211610
    Description:

    In this paper, a discussion of the three papers from the US Census Bureau special compilation is presented.

    Release date: 2011-12-21

  • Articles and reports: 65-507-M2011011
    Description:

    This issue presents statistics, derived from the Importer Register Database, on importing establishments for the years 2002 to 2009. This Importer Register Database provides importer statistics such as the number of importers and the value of their imports by industry, importer size, origin and province of residence.

    The establishment is the statistical unit of measure. Consequently, any reference made here to "importers" represents "statistical establishments that imported." Inclusion in the database requires that an establishment has imported merchandise in at least one year from 2002 to 2009. If an establishment does not import in a given year, that establishment is not included in the Register for that year.

    This report is divided into four sections: "Highlights" consist of an overview of results of the 2009 Importer Register Database; "Findings" contains more detailed analyses of the Importer Register Database; "Methodology, Data concepts and definitions" outlines the estimation methods and limitations as well as the fundamental principles of the Importer Register Database; and "Data tables" contain tabular data for the years from 2002 to 2009.

    Release date: 2011-12-06

  • Articles and reports: 65-507-M2010010
    Geography: Province or territory
    Description:

    This issue presents exporter statistics from 1996 to 2009 including the number of exporters, the value of their domestic exports by industry, exporter size, destination and province of residence as well as employment statistics of exporting establishments for the year 2009. The data in this issue are at the establishment level and are derived from the Exporter Register Database.

    Release date: 2011-10-28

  • 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: 12-001-X201100111444
    Description:

    Data linkage is the act of bringing together records that are believed to belong to the same unit (e.g., person or business) from two or more files. It is a very common way to enhance dimensions such as time and breadth or depth of detail. Data linkage is often not an error-free process and can lead to linking a pair of records that do not belong to the same unit. There is an explosion of record linkage applications, yet there has been little work on assuring the quality of analyses using such linked files. Naively treating such a linked file as if it were linked without errors will, in general, lead to biased estimates. This paper develops a maximum likelihood estimator for contingency tables and logistic regression with incorrectly linked records. The estimation technique is simple and is implemented using the well-known EM algorithm. A well known method of linking records in the present context is probabilistic data linking. The paper demonstrates the effectiveness of the proposed estimators in an empirical study which uses probabilistic data linkage.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201100111445
    Description:

    In this paper we study small area estimation using area level models. We first consider the Fay-Herriot model (Fay and Herriot 1979) for the case of smoothed known sampling variances and the You-Chapman model (You and Chapman 2006) for the case of sampling variance modeling. Then we consider hierarchical Bayes (HB) spatial models that extend the Fay-Herriot and You-Chapman models by capturing both the geographically unstructured heterogeneity and spatial correlation effects among areas for local smoothing. The proposed models are implemented using the Gibbs sampling method for fully Bayesian inference. We apply the proposed models to the analysis of health survey data and make comparisons among the HB model-based estimates and direct design-based estimates. Our results have shown that the HB model-based estimates perform much better than the direct estimates. In addition, the proposed area level spatial models achieve smaller CVs than the Fay-Herriot and You-Chapman models, particularly for the areas with three or more neighbouring areas. Bayesian model comparison and model fit analysis are also presented.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201100111446
    Description:

    Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory performance of the method.

    Release date: 2011-06-29

  • Articles and reports: 12-001-X201100111447
    Description:

    This paper introduces a R-package for the stratification of a survey population using a univariate stratification variable X and for the calculation of stratum sample sizes. Non iterative methods such as the cumulative root frequency method and the geometric stratum boundaries are implemented. Optimal designs, with stratum boundaries that minimize either the CV of the simple expansion estimator for a fixed sample size n or the n value for a fixed CV can be constructed. Two iterative algorithms are available to find the optimal stratum boundaries. The design can feature a user defined certainty stratum where all the units are sampled. Take-all and take-none strata can be included in the stratified design as they might lead to smaller sample sizes. The sample size calculations are based on the anticipated moments of the survey variable Y, given the stratification variable X. The package handles conditional distributions of Y given X that are either a heteroscedastic linear model, or a log-linear model. Stratum specific non-response can be accounted for in the design construction and in the sample size calculations.

    Release date: 2011-06-29
Reference (4)

Reference (4) ((4 results))

  • Surveys and statistical programs – Documentation: 12-001-X201100211607
    Description:

    This paper describes recent developments in adaptive sampling strategies and introduces new variations on those strategies. Recent developments described included targeted random walk designs and adaptive web sampling. These designs are particularly suited for sampling in networks; for example, for finding a sample of people from a hidden human population by following social links from sample individuals to find additional members of the hidden population to add to the sample. Each of these designs can also be translated into spatial settings to produce flexible new spatial adaptive strategies for sampling unevenly distributed populations. Variations on these sampling strategies include versions in which the network or spatial links have unequal weights and are followed with unequal probabilities.

    Release date: 2011-12-21

  • Notices and consultations: 13-605-X201100311491
    Description:

    This paper provides a preview of the comprehensive (historical) revision of the Canadian System National Accounts to be released beginning in June 2012. The last revision of this scope took place in 1997. The paper highlights the changes resulting from the adoption of SNA2008 which is the revised international standard for national accounting, along with statistical revisions arising from new and improved source data and methodologies. Updates to the classification systems used in the Canadian System of National Accounts are also presented along with a list of changes planned for 2014.

    Release date: 2011-06-20

  • Surveys and statistical programs – Documentation: 11-010-X201100611501
    Description:

    A detailed exposition of how the pattern of quarterly growth affects the average annual growth rate, including the relative importance of these quarters in determining growth These basic principles are applied to monthly and quarterly growth.

    Release date: 2011-06-16

  • Surveys and statistical programs – Documentation: 13-605-X201100211471
    Description:

    This paper presents the background, methodological change and implementation of the revised real import and export adjustments that account for exchange rate fluctuations.

    Release date: 2011-05-30
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