Keyword search

Results

All (172)

All (172) (0 to 10 of 172 results)

1. Estimating municipal life expectancy and health-adjusted life expectancy in Canada, 2019 and 2020
Articles and reports: 82-003-X202500800001
Description: Data measuring life expectancy (LE) and health-adjusted life expectancy (HALE) in Canada are available for large geographical areas, such as provinces, territories, and health regions. However, to date, no study has analyzed LE and HALE at the municipal level. To address issues related to sparse administrative and survey data in small geographic areas, this study applies multilevel regression models and poststratification methods that have been shown to provide reliable estimates of population- and small area-level quantities from health surveys.
Release date: 2025-08-20
2. Survey data integration for regression analysis using model calibration
Articles and reports: 12-001-X202300100002
Description: We consider regression analysis in the context of data integration. To combine partial information from external sources, we employ the idea of model calibration which introduces a “working” reduced model based on the observed covariates. The working reduced model is not necessarily correctly specified but can be a useful device to incorporate the partial information from the external data. The actual implementation is based on a novel application of the information projection and model calibration weighting. The proposed method is particularly attractive for combining information from several sources with different missing patterns. The proposed method is applied to a real data example combining survey data from Korean National Health and Nutrition Examination Survey and big data from National Health Insurance Sharing Service in Korea.
Release date: 2023-06-30
3. Relative Performance of Methods Based on Model-Assisted Survey Regression Estimation Archived
Articles and reports: 11-522-X202100100009
Description:
Use of auxiliary data to improve the efficiency of estimators of totals and means through model-assisted survey regression estimation has received considerable attention in recent years. Generalized regression (GREG) estimators, based on a working linear regression model, are currently used in establishment surveys at Statistics Canada and several other statistical agencies. GREG estimators use common survey weights for all study variables and calibrate to known population totals of auxiliary variables. Increasingly, many auxiliary variables are available, some of which may be extraneous. This leads to unstable GREG weights when all the available auxiliary variables, including interactions among categorical variables, are used in the working linear regression model. On the other hand, new machine learning methods, such as regression trees and lasso, automatically select significant auxiliary variables and lead to stable nonnegative weights and possible efficiency gains over GREG. In this paper, a simulation study, based on a real business survey sample data set treated as the target population, is conducted to study the relative performance of GREG, regression trees and lasso in terms of efficiency of the estimators.
Key Words: Model assisted inference; calibration estimation; model selection; generalized regression estimator.

Release date: 2021-10-29
4. Refugees and Canadian Post-Secondary Education: Characteristics and Economic Outcomes in Comparison Archived
Articles and reports: 89-657-X2018001
Description:
This study draws on data from the Longitudinal Immigration Database to examine participation in Canadian post-secondary education (PSE) among adult immigrants in the 2002-2005 landing cohort, with an explicit focus on resettled refugees. The study describes the demographic characteristics of participants, the qualities of participation, and the economic returns on investment in Canadian PSE. It also employs multivariate regression analysis to further examine the effects of participation in Canadian training on employment incidence and the income of those employed, while controlling for other factors associated with successful economic integration.
Release date: 2018-11-14
5. A comparison between nonparametric estimators for finite population distribution functions Archived
Articles and reports: 12-001-X201600114541
Description:
In this work we compare nonparametric estimators for finite population distribution functions based on two types of fitted values: the fitted values from the well-known Kuo estimator and a modified version of them, which incorporates a nonparametric estimate for the mean regression function. For each type of fitted values we consider the corresponding model-based estimator and, after incorporating design weights, the corresponding generalized difference estimator. We show under fairly general conditions that the leading term in the model mean square error is not affected by the modification of the fitted values, even though it slows down the convergence rate for the model bias. Second order terms of the model mean square errors are difficult to obtain and will not be derived in the present paper. It remains thus an open question whether the modified fitted values bring about some benefit from the model-based perspective. We discuss also design-based properties of the estimators and propose a variance estimator for the generalized difference estimator based on the modified fitted values. Finally, we perform a simulation study. The simulation results suggest that the modified fitted values lead to a considerable reduction of the design mean square error if the sample size is small.
Release date: 2016-06-22
6. A note on regression estimation with unknown population size Archived
Articles and reports: 12-001-X201600114543
Description:
The regression estimator is extensively used in practice because it can improve the reliability of the estimated parameters of interest such as means or totals. It uses control totals of variables known at the population level that are included in the regression set up. In this paper, we investigate the properties of the regression estimator that uses control totals estimated from the sample, as well as those known at the population level. This estimator is compared to the regression estimators that strictly use the known totals both theoretically and via a simulation study.
Release date: 2016-06-22
7. A short note on quantile and expectile estimation in unequal probability samples Archived
Articles and reports: 12-001-X201600114545
Description:
The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.
Release date: 2016-06-22
8. The Impact of Annual Wages on Interprovincial Mobility, Interprovincial Employment, and Job Vacancies Archived
Articles and reports: 11F0019M2016376
Geography: Canada, Province or territory
Description: The degree to which workers move across geographic areas in response to emerging employment opportunities or negative labour demand shocks is a key element in the adjustment process of an economy, and its ability to reach a desired allocation of resources.

This study estimates the causal impact of real after-tax annual wages and salaries on the propensity of young men to migrate to Alberta or to accept jobs in that province while maintaining residence in their home province. To do so, it exploits the cross-provincial variation in earnings growth plausibly induced by increases in world oil prices that occurred during the 2000s.
Release date: 2016-04-11
9. Do Workplace Pensions Crowd Out Other Retirement Savings? Evidence from Canadian Tax Records Archived
Articles and reports: 11F0019M2015371
Description:
This paper investigates whether registered pension plans (RPPs) help households prepare financially for retirement or simply substitute for other forms of private saving. This issue is addressed using a panel of 1.8 million Canadian households, from 1991 to 2010, which appear in the Longitudinal Administrative Databank. The analysis controls for correlations in savings across accounts due to unobserved tastes for saving by exploiting the fact that employer contribution rates increase discontinuously on earnings above the average industrial wage, a unique feature of occupational pensions in Canada, the effect being estimated in a Regression Kink Design.
Release date: 2015-12-21
10. A design effect measure for calibration weighting in single-stage samples Archived
Articles and reports: 12-001-X201500214236
Description:
We propose a model-assisted extension of weighting design-effect measures. We develop a summary-level statistic for different variables of interest, in single-stage sampling and under calibration weight adjustments. Our proposed design effect measure captures the joint effects of a non-epsem sampling design, unequal weights produced using calibration adjustments, and the strength of the association between an analysis variable and the auxiliaries used in calibration. We compare our proposed measure to existing design effect measures in simulations using variables like those collected in establishment surveys and telephone surveys of households.
Release date: 2015-12-17

Data (0)

Data (0) (0 results)

No content available at this time.

Analysis (172)

Analysis (172) (0 to 10 of 172 results)

1. Estimating municipal life expectancy and health-adjusted life expectancy in Canada, 2019 and 2020
Articles and reports: 82-003-X202500800001
Description: Data measuring life expectancy (LE) and health-adjusted life expectancy (HALE) in Canada are available for large geographical areas, such as provinces, territories, and health regions. However, to date, no study has analyzed LE and HALE at the municipal level. To address issues related to sparse administrative and survey data in small geographic areas, this study applies multilevel regression models and poststratification methods that have been shown to provide reliable estimates of population- and small area-level quantities from health surveys.
Release date: 2025-08-20
2. Survey data integration for regression analysis using model calibration
Articles and reports: 12-001-X202300100002
Description: We consider regression analysis in the context of data integration. To combine partial information from external sources, we employ the idea of model calibration which introduces a “working” reduced model based on the observed covariates. The working reduced model is not necessarily correctly specified but can be a useful device to incorporate the partial information from the external data. The actual implementation is based on a novel application of the information projection and model calibration weighting. The proposed method is particularly attractive for combining information from several sources with different missing patterns. The proposed method is applied to a real data example combining survey data from Korean National Health and Nutrition Examination Survey and big data from National Health Insurance Sharing Service in Korea.
Release date: 2023-06-30
3. Relative Performance of Methods Based on Model-Assisted Survey Regression Estimation Archived
Articles and reports: 11-522-X202100100009
Description:
Use of auxiliary data to improve the efficiency of estimators of totals and means through model-assisted survey regression estimation has received considerable attention in recent years. Generalized regression (GREG) estimators, based on a working linear regression model, are currently used in establishment surveys at Statistics Canada and several other statistical agencies. GREG estimators use common survey weights for all study variables and calibrate to known population totals of auxiliary variables. Increasingly, many auxiliary variables are available, some of which may be extraneous. This leads to unstable GREG weights when all the available auxiliary variables, including interactions among categorical variables, are used in the working linear regression model. On the other hand, new machine learning methods, such as regression trees and lasso, automatically select significant auxiliary variables and lead to stable nonnegative weights and possible efficiency gains over GREG. In this paper, a simulation study, based on a real business survey sample data set treated as the target population, is conducted to study the relative performance of GREG, regression trees and lasso in terms of efficiency of the estimators.
Key Words: Model assisted inference; calibration estimation; model selection; generalized regression estimator.

Release date: 2021-10-29
4. Refugees and Canadian Post-Secondary Education: Characteristics and Economic Outcomes in Comparison Archived
Articles and reports: 89-657-X2018001
Description:
This study draws on data from the Longitudinal Immigration Database to examine participation in Canadian post-secondary education (PSE) among adult immigrants in the 2002-2005 landing cohort, with an explicit focus on resettled refugees. The study describes the demographic characteristics of participants, the qualities of participation, and the economic returns on investment in Canadian PSE. It also employs multivariate regression analysis to further examine the effects of participation in Canadian training on employment incidence and the income of those employed, while controlling for other factors associated with successful economic integration.
Release date: 2018-11-14
5. A comparison between nonparametric estimators for finite population distribution functions Archived
Articles and reports: 12-001-X201600114541
Description:
In this work we compare nonparametric estimators for finite population distribution functions based on two types of fitted values: the fitted values from the well-known Kuo estimator and a modified version of them, which incorporates a nonparametric estimate for the mean regression function. For each type of fitted values we consider the corresponding model-based estimator and, after incorporating design weights, the corresponding generalized difference estimator. We show under fairly general conditions that the leading term in the model mean square error is not affected by the modification of the fitted values, even though it slows down the convergence rate for the model bias. Second order terms of the model mean square errors are difficult to obtain and will not be derived in the present paper. It remains thus an open question whether the modified fitted values bring about some benefit from the model-based perspective. We discuss also design-based properties of the estimators and propose a variance estimator for the generalized difference estimator based on the modified fitted values. Finally, we perform a simulation study. The simulation results suggest that the modified fitted values lead to a considerable reduction of the design mean square error if the sample size is small.
Release date: 2016-06-22
6. A note on regression estimation with unknown population size Archived
Articles and reports: 12-001-X201600114543
Description:
The regression estimator is extensively used in practice because it can improve the reliability of the estimated parameters of interest such as means or totals. It uses control totals of variables known at the population level that are included in the regression set up. In this paper, we investigate the properties of the regression estimator that uses control totals estimated from the sample, as well as those known at the population level. This estimator is compared to the regression estimators that strictly use the known totals both theoretically and via a simulation study.
Release date: 2016-06-22
7. A short note on quantile and expectile estimation in unequal probability samples Archived
Articles and reports: 12-001-X201600114545
Description:
The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.
Release date: 2016-06-22
8. The Impact of Annual Wages on Interprovincial Mobility, Interprovincial Employment, and Job Vacancies Archived
Articles and reports: 11F0019M2016376
Geography: Canada, Province or territory
Description: The degree to which workers move across geographic areas in response to emerging employment opportunities or negative labour demand shocks is a key element in the adjustment process of an economy, and its ability to reach a desired allocation of resources.

This study estimates the causal impact of real after-tax annual wages and salaries on the propensity of young men to migrate to Alberta or to accept jobs in that province while maintaining residence in their home province. To do so, it exploits the cross-provincial variation in earnings growth plausibly induced by increases in world oil prices that occurred during the 2000s.
Release date: 2016-04-11
9. Do Workplace Pensions Crowd Out Other Retirement Savings? Evidence from Canadian Tax Records Archived
Articles and reports: 11F0019M2015371
Description:
This paper investigates whether registered pension plans (RPPs) help households prepare financially for retirement or simply substitute for other forms of private saving. This issue is addressed using a panel of 1.8 million Canadian households, from 1991 to 2010, which appear in the Longitudinal Administrative Databank. The analysis controls for correlations in savings across accounts due to unobserved tastes for saving by exploiting the fact that employer contribution rates increase discontinuously on earnings above the average industrial wage, a unique feature of occupational pensions in Canada, the effect being estimated in a Regression Kink Design.
Release date: 2015-12-21
10. A design effect measure for calibration weighting in single-stage samples Archived
Articles and reports: 12-001-X201500214236
Description:
We propose a model-assisted extension of weighting design-effect measures. We develop a summary-level statistic for different variables of interest, in single-stage sampling and under calibration weight adjustments. Our proposed design effect measure captures the joint effects of a non-epsem sampling design, unequal weights produced using calibration adjustments, and the strength of the association between an analysis variable and the auxiliaries used in calibration. We compare our proposed measure to existing design effect measures in simulations using variables like those collected in establishment surveys and telephone surveys of households.
Release date: 2015-12-17

Reference (0)

Reference (0) (0 results)

No content available at this time.

Date modified:: 2026-08-13