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- Selected: L (26)
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Results
All (26)
All (26) (0 to 10 of 26 results)
- Articles and reports: 67F0001M2004022Geography: CanadaDescription:
Canada's balance of payments with the United States should be, in principle, the mirror image of the U.S. balance of payments with Canada. In practice, however, the two countries' statistics have conceptual, methodological and data differences.
Each year, the two countries' balance of payments current accounts are reconciled to reflect how the estimates would appear if both countries used common definitions, methodologies and data sources. Such reconciliation is important because of the extensive economic links between the two countries and the need to explain differences in their published official bilateral estimates.
Release date: 2004-12-22 - 2. Characteristics of Firms That Grow from Small to Medium Size: Growth Factors - Interviews and Measurability ArchivedArticles and reports: 88F0006X2004021Description:
This working paper outlines the critical growth factors resulting from interviews with senior business managers. It also explores additional sources of data and makes recommendations for the content of possible future surveys.
Release date: 2004-12-10 - 3. Who Pursues Postsecondary Education, Who Leaves and Why? Results from the Youth in Transition Survey ArchivedArticles and reports: 81-595-M2004026Geography: CanadaDescription:
This report examines factors related to entering college or university as well as to leaving postsecondary education prior to completion.
Release date: 2004-11-18 - Articles and reports: 88-003-X20040037436Geography: CanadaDescription:
This study examined the difference in adoption rates between firms that reported high employment growth and firms that did not.
Release date: 2004-10-29 - Articles and reports: 88-003-X20040037439Geography: CanadaDescription:
This article provides an overview of research and development expenditures by the two countries' manufacturing sectors and then examines the data by industry to measure the relative research and development intensity of Canada's manufacturing industries compared with those of the United States.
Release date: 2004-10-29 - Articles and reports: 88-003-X20040037441Geography: CanadaDescription:
This article examines average research and development spending per firm and revenue growth. Using data from the Survey of Research and Development in Canadian Industry, it explores differences in research and development spending and revenue growth between high-growth and non-high-growth firms that reported strong employment growth.
Release date: 2004-10-29 - 7. Saving for postsecondary education ArchivedArticles and reports: 75-001-X200410713123Geography: CanadaDescription:
This study looks at the decision of parents to save, and amounts saved, for the future education of children aged under 19 years in 2002. A model is used to estimate cumulative parental savings, taking into consideration characteristics of the family and the child, aspirations and involvement of parents, awareness of saving incentive programs, and expectations about grant programs.
Release date: 2004-09-21 - 8. Comparison of design-based and model-based methods in analyzing complex health survey data: A case study ArchivedArticles and reports: 11-522-X20020016708Description:
In this paper, we discuss the analysis of complex health survey data by using multivariate modelling techniques. Main interests are in various design-based and model-based methods that aim at accounting for the design complexities, including clustering, stratification and weighting. Methods covered include generalized linear modelling based on pseudo-likelihood and generalized estimating equations, linear mixed models estimated by restricted maximum likelihood, and hierarchical Bayes techniques using Markov Chain Monte Carlo (MCMC) methods. The methods will be compared empirically, using data from an extensive health interview and examination survey conducted in Finland in 2000 (Health 2000 Study).
The data of the Health 2000 Study were collected using personal interviews, questionnaires and clinical examinations. A stratified two-stage cluster sampling design was used in the survey. The sampling design involved positive intra-cluster correlation for many study variables. For a closer investigation, we selected a small number of study variables from the health interview and health examination phases. In many cases, the different methods produced similar numerical results and supported similar statistical conclusions. Methods that failed to account for the design complexities sometimes led to conflicting conclusions. We also discuss the application of the methods in this paper by using standard statistical software products.
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016716Description:
Missing data are a constant problem in large-scale surveys. Such incompleteness is usually dealt with either by restricting the analysis to the cases with complete records or by imputing, for each missing item, an efficiently estimated value. The deficiencies of these approaches will be discussed in this paper, especially in the context of estimating a large number of quantities. The main part of the paper will describe two examples of analyses using multiple imputation.
In the first, the International Labour Organization (ILO) employment status is imputed in the British Labour Force Survey by a Bayesian bootstrap method. It is an adaptation of the hot-deck method, which seeks to fully exploit the auxiliary information. Important auxiliary information is given by the previous ILO status, when available, and the standard demographic variables.
Missing data can be interpreted more generally, as in the framework of the expectation maximization (EM) algorithm. The second example is from the Scottish House Condition Survey, and its focus is on the inconsistency of the surveyors. The surveyors assess the sampled dwelling units on a large number of elements or features of the dwelling, such as internal walls, roof and plumbing, that are scored and converted to a summarizing 'comprehensive repair cost.' The level of inconsistency is estimated from the discrepancies between the pairs of assessments of doubly surveyed dwellings. The principal research questions concern the amount of information that is lost as a result of the inconsistency and whether the naive estimators that ignore the inconsistency are unbiased. The problem is solved by multiple imputation, generating plausible scores for all the dwellings in the survey.
Release date: 2004-09-13 - 10. Area-level models using data from multiple surveys ArchivedArticles and reports: 11-522-X20020016717Description:
In the United States, the National Health and Nutrition Examination Survey (NHANES) is linked to the National Health Interview Survey (NHIS) at the primary sampling unit level (the same counties, but not necessarily the same persons, are in both surveys). The NHANES examines about 5,000 persons per year, while the NHIS samples about 100,000 persons per year. In this paper, we present and develop properties of models that allow NHIS and administrative data to be used as auxiliary information for estimating quantities of interest in the NHANES. The methodology, related to Fay-Herriot (1979) small-area models and to calibration estimators in Deville and Sarndal (1992), accounts for the survey designs in the error structure.
Release date: 2004-09-13
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Articles and reports (26)
Articles and reports (26) (0 to 10 of 26 results)
- Articles and reports: 67F0001M2004022Geography: CanadaDescription:
Canada's balance of payments with the United States should be, in principle, the mirror image of the U.S. balance of payments with Canada. In practice, however, the two countries' statistics have conceptual, methodological and data differences.
Each year, the two countries' balance of payments current accounts are reconciled to reflect how the estimates would appear if both countries used common definitions, methodologies and data sources. Such reconciliation is important because of the extensive economic links between the two countries and the need to explain differences in their published official bilateral estimates.
Release date: 2004-12-22 - 2. Characteristics of Firms That Grow from Small to Medium Size: Growth Factors - Interviews and Measurability ArchivedArticles and reports: 88F0006X2004021Description:
This working paper outlines the critical growth factors resulting from interviews with senior business managers. It also explores additional sources of data and makes recommendations for the content of possible future surveys.
Release date: 2004-12-10 - 3. Who Pursues Postsecondary Education, Who Leaves and Why? Results from the Youth in Transition Survey ArchivedArticles and reports: 81-595-M2004026Geography: CanadaDescription:
This report examines factors related to entering college or university as well as to leaving postsecondary education prior to completion.
Release date: 2004-11-18 - Articles and reports: 88-003-X20040037436Geography: CanadaDescription:
This study examined the difference in adoption rates between firms that reported high employment growth and firms that did not.
Release date: 2004-10-29 - Articles and reports: 88-003-X20040037439Geography: CanadaDescription:
This article provides an overview of research and development expenditures by the two countries' manufacturing sectors and then examines the data by industry to measure the relative research and development intensity of Canada's manufacturing industries compared with those of the United States.
Release date: 2004-10-29 - Articles and reports: 88-003-X20040037441Geography: CanadaDescription:
This article examines average research and development spending per firm and revenue growth. Using data from the Survey of Research and Development in Canadian Industry, it explores differences in research and development spending and revenue growth between high-growth and non-high-growth firms that reported strong employment growth.
Release date: 2004-10-29 - 7. Saving for postsecondary education ArchivedArticles and reports: 75-001-X200410713123Geography: CanadaDescription:
This study looks at the decision of parents to save, and amounts saved, for the future education of children aged under 19 years in 2002. A model is used to estimate cumulative parental savings, taking into consideration characteristics of the family and the child, aspirations and involvement of parents, awareness of saving incentive programs, and expectations about grant programs.
Release date: 2004-09-21 - 8. Comparison of design-based and model-based methods in analyzing complex health survey data: A case study ArchivedArticles and reports: 11-522-X20020016708Description:
In this paper, we discuss the analysis of complex health survey data by using multivariate modelling techniques. Main interests are in various design-based and model-based methods that aim at accounting for the design complexities, including clustering, stratification and weighting. Methods covered include generalized linear modelling based on pseudo-likelihood and generalized estimating equations, linear mixed models estimated by restricted maximum likelihood, and hierarchical Bayes techniques using Markov Chain Monte Carlo (MCMC) methods. The methods will be compared empirically, using data from an extensive health interview and examination survey conducted in Finland in 2000 (Health 2000 Study).
The data of the Health 2000 Study were collected using personal interviews, questionnaires and clinical examinations. A stratified two-stage cluster sampling design was used in the survey. The sampling design involved positive intra-cluster correlation for many study variables. For a closer investigation, we selected a small number of study variables from the health interview and health examination phases. In many cases, the different methods produced similar numerical results and supported similar statistical conclusions. Methods that failed to account for the design complexities sometimes led to conflicting conclusions. We also discuss the application of the methods in this paper by using standard statistical software products.
Release date: 2004-09-13 - Articles and reports: 11-522-X20020016716Description:
Missing data are a constant problem in large-scale surveys. Such incompleteness is usually dealt with either by restricting the analysis to the cases with complete records or by imputing, for each missing item, an efficiently estimated value. The deficiencies of these approaches will be discussed in this paper, especially in the context of estimating a large number of quantities. The main part of the paper will describe two examples of analyses using multiple imputation.
In the first, the International Labour Organization (ILO) employment status is imputed in the British Labour Force Survey by a Bayesian bootstrap method. It is an adaptation of the hot-deck method, which seeks to fully exploit the auxiliary information. Important auxiliary information is given by the previous ILO status, when available, and the standard demographic variables.
Missing data can be interpreted more generally, as in the framework of the expectation maximization (EM) algorithm. The second example is from the Scottish House Condition Survey, and its focus is on the inconsistency of the surveyors. The surveyors assess the sampled dwelling units on a large number of elements or features of the dwelling, such as internal walls, roof and plumbing, that are scored and converted to a summarizing 'comprehensive repair cost.' The level of inconsistency is estimated from the discrepancies between the pairs of assessments of doubly surveyed dwellings. The principal research questions concern the amount of information that is lost as a result of the inconsistency and whether the naive estimators that ignore the inconsistency are unbiased. The problem is solved by multiple imputation, generating plausible scores for all the dwellings in the survey.
Release date: 2004-09-13 - 10. Area-level models using data from multiple surveys ArchivedArticles and reports: 11-522-X20020016717Description:
In the United States, the National Health and Nutrition Examination Survey (NHANES) is linked to the National Health Interview Survey (NHIS) at the primary sampling unit level (the same counties, but not necessarily the same persons, are in both surveys). The NHANES examines about 5,000 persons per year, while the NHIS samples about 100,000 persons per year. In this paper, we present and develop properties of models that allow NHIS and administrative data to be used as auxiliary information for estimating quantities of interest in the NHANES. The methodology, related to Fay-Herriot (1979) small-area models and to calibration estimators in Deville and Sarndal (1992), accounts for the survey designs in the error structure.
Release date: 2004-09-13
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