Analysis

A century of trust, safety, facts

Statistics Canada's Trust Centre: Learn how Statistics Canada keeps your data safe and protects your privacy.

Filter results by

Search Help
Currently selected filters that can be removed

Keyword(s)

Year of publication

1 facets displayed. 1 facets selected.
Sort Help
entries

Results

All (36)

All (36) (0 to 10 of 36 results)

  • Articles and reports: 12-001-X199200214480
    Description:

    We consider the problem of estimating the “cost weights” and “relative importances” of different item strata for the local market basket areas. The estimation of these parameters is needed to construct the U.S. Consumer Price Index Numbers. We use multivariate models to construct composite estimators which combine information from relevant sources. The mean squared errors (MSE) of the proposed and the existing estimators are estimated using the repeated half samples available from the survey. Based on our numerical results, the proposed estimators seem to be superior to the existing estimators.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214481
    Description:

    Using data from a survey of U.S. Census Bureau interviewers, this paper examines whether experienced interviewers achieve higher response rates than inexperienced interviewers, controlling for differences in survey design and attributes of the populations assigned to them. After demonstrating that the relationship is positive and curvilinear, it attempts to explain the mechanisms by which experienced interviewers achieve these rates and elaborate the nature of the relationship. It examines what behaviors and attitudes underlie the higher success, with the hope that they might be instilled in trainees.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214482
    Description:

    Motivated by a business survey design at Statistics Canada, we formulate the problem of sample allocation for a general two-phase survey design as a constrained nonlinear programming problem. By exploiting its mathematical structure, we propose a solution method that consists of iterations between two subproblems that are computationally much simpler. Using an approximate solution as a starting value, the proposed method works very well in an empirical study.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214483
    Description:

    In almost all large surveys, some form of imputation is used. This paper develops a method for variance estimation when single (as opposed to multiple) imputation is used to create a completed data set. Imputation will never reproduce the true values (except in truly exceptional cases). The total error of the survey estimate is viewed in this paper as the sum of sampling error and imputation error. Consequently, an overall variance is derived as the sum of a sampling variance and an imputation variance. The principal theme is the estimation of these two components, using the data after imputation, that is, the actually observed values and the imputed values. The approach is model assisted in the sense that the model implied by the imputation method and the randomization distribution used for sample selection will together determine the appearance of the variance estimators. The theoretical findings are confirmed by a Monte Carlo simulation.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214484
    Description:

    Maximum likelihood estimation from complex sample data requires additional modeling due to the information in the sample selection. Alternatively, pseudo maximum likelihood methods that consist of maximizing estimates of the census score function can be applied. In this article we review some of the approaches considered in the literature and compare them with a new approach derived from the ideas of ‘weighted distributions’. The focus of the comparisons is on situations where some or all of the design variables are unknown or misspecified. The results obtained for the new method are encouraging, but the study is limited so far to simple situations.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214485
    Description:

    Godambe and Thompson (1986) define and develop simultaneous optimal estimation of superpopulation and finite population parameters based on a superpopulation model and a survey sampling design. Their theory defines the finite population parameter, \theta_N, as the solution of the optimal estimating equation for the superpopulation parameter \theta; however, some other finite population parameter, \phi, may be of interest. We propose to extend the superpopulation model in such a way that the parameter of interest, \phi, is a known function of \theta_N, say \phi = f (\theta_N). Then \phi is optimally estimated by f (\theta_s), where \theta_s is the optimal estimator of \theta_N, as given by Godambe and Thompson (1986), based on the sample s and the sampling design.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214486
    Description:

    Resampling methods for inference with complex survey data include the jackknife, balanced repeated replication (BRR) and the bootstrap. We review some recent work on these methods for standard error and confidence interval estimation. Some empirical results for non-smooth statistics are also given.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214487
    Description:

    This paper reviews the idea of robustness for randomisation and model-based inference for descriptive and analytic surveys. The lack of robustness for model-based procedures can be partially overcome by careful design. In this paper a robust model-based approach to analysis is proposed based on smoothing methods.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214488
    Description:

    In many finite population sampling problems the design that is optimal in the sense of minimizing the variance of the best linear unbiased estimator under a particular working model is bad in the sense of robustness - it leaves the estimator extremely vulnerable to bias if the working model is incorrect. However there are some important models under which one design provides both efficiency and robustness. We present a theorem that identifies such models and their optimal designs.

    Release date: 1992-12-15

  • 10. Job-related moves Archived
    Articles and reports: 75-001-X1992004101
    Geography: Canada
    Description:

    The characteristics of people who moved in 1987 to look for work, start a new job or take a transfer are profiled.

    Release date: 1992-12-01
Stats in brief (1)

Stats in brief (1) ((1 result))

  • Stats in brief: 75-001-X199200387
    Geography: Canada
    Description:

    An examination of trends in unemployment rate data as far back as 1921.

    Release date: 1992-09-01
Articles and reports (35)

Articles and reports (35) (0 to 10 of 35 results)

  • Articles and reports: 12-001-X199200214480
    Description:

    We consider the problem of estimating the “cost weights” and “relative importances” of different item strata for the local market basket areas. The estimation of these parameters is needed to construct the U.S. Consumer Price Index Numbers. We use multivariate models to construct composite estimators which combine information from relevant sources. The mean squared errors (MSE) of the proposed and the existing estimators are estimated using the repeated half samples available from the survey. Based on our numerical results, the proposed estimators seem to be superior to the existing estimators.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214481
    Description:

    Using data from a survey of U.S. Census Bureau interviewers, this paper examines whether experienced interviewers achieve higher response rates than inexperienced interviewers, controlling for differences in survey design and attributes of the populations assigned to them. After demonstrating that the relationship is positive and curvilinear, it attempts to explain the mechanisms by which experienced interviewers achieve these rates and elaborate the nature of the relationship. It examines what behaviors and attitudes underlie the higher success, with the hope that they might be instilled in trainees.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214482
    Description:

    Motivated by a business survey design at Statistics Canada, we formulate the problem of sample allocation for a general two-phase survey design as a constrained nonlinear programming problem. By exploiting its mathematical structure, we propose a solution method that consists of iterations between two subproblems that are computationally much simpler. Using an approximate solution as a starting value, the proposed method works very well in an empirical study.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214483
    Description:

    In almost all large surveys, some form of imputation is used. This paper develops a method for variance estimation when single (as opposed to multiple) imputation is used to create a completed data set. Imputation will never reproduce the true values (except in truly exceptional cases). The total error of the survey estimate is viewed in this paper as the sum of sampling error and imputation error. Consequently, an overall variance is derived as the sum of a sampling variance and an imputation variance. The principal theme is the estimation of these two components, using the data after imputation, that is, the actually observed values and the imputed values. The approach is model assisted in the sense that the model implied by the imputation method and the randomization distribution used for sample selection will together determine the appearance of the variance estimators. The theoretical findings are confirmed by a Monte Carlo simulation.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214484
    Description:

    Maximum likelihood estimation from complex sample data requires additional modeling due to the information in the sample selection. Alternatively, pseudo maximum likelihood methods that consist of maximizing estimates of the census score function can be applied. In this article we review some of the approaches considered in the literature and compare them with a new approach derived from the ideas of ‘weighted distributions’. The focus of the comparisons is on situations where some or all of the design variables are unknown or misspecified. The results obtained for the new method are encouraging, but the study is limited so far to simple situations.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214485
    Description:

    Godambe and Thompson (1986) define and develop simultaneous optimal estimation of superpopulation and finite population parameters based on a superpopulation model and a survey sampling design. Their theory defines the finite population parameter, \theta_N, as the solution of the optimal estimating equation for the superpopulation parameter \theta; however, some other finite population parameter, \phi, may be of interest. We propose to extend the superpopulation model in such a way that the parameter of interest, \phi, is a known function of \theta_N, say \phi = f (\theta_N). Then \phi is optimally estimated by f (\theta_s), where \theta_s is the optimal estimator of \theta_N, as given by Godambe and Thompson (1986), based on the sample s and the sampling design.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214486
    Description:

    Resampling methods for inference with complex survey data include the jackknife, balanced repeated replication (BRR) and the bootstrap. We review some recent work on these methods for standard error and confidence interval estimation. Some empirical results for non-smooth statistics are also given.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214487
    Description:

    This paper reviews the idea of robustness for randomisation and model-based inference for descriptive and analytic surveys. The lack of robustness for model-based procedures can be partially overcome by careful design. In this paper a robust model-based approach to analysis is proposed based on smoothing methods.

    Release date: 1992-12-15

  • Articles and reports: 12-001-X199200214488
    Description:

    In many finite population sampling problems the design that is optimal in the sense of minimizing the variance of the best linear unbiased estimator under a particular working model is bad in the sense of robustness - it leaves the estimator extremely vulnerable to bias if the working model is incorrect. However there are some important models under which one design provides both efficiency and robustness. We present a theorem that identifies such models and their optimal designs.

    Release date: 1992-12-15

  • 10. Job-related moves Archived
    Articles and reports: 75-001-X1992004101
    Geography: Canada
    Description:

    The characteristics of people who moved in 1987 to look for work, start a new job or take a transfer are profiled.

    Release date: 1992-12-01
Journals and periodicals (0)

Journals and periodicals (0) (0 results)

No content available at this time.

Date modified: