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All (19)

All (19) (0 to 10 of 19 results)

  • 1. Surveying Aboriginal and Torres Strait islander peoples: Strategies and methodologies of the Australian Bureau of Statistics Archived
    Articles and reports: 11-522-X20040018654
    Description:

    In Australia, cultural considerations influence the statistical activity with regards to Indigenous population. The paper discusses survey designs, operations, estimation and dissemination.

    Release date: 2005-10-27
  • 2. Aboriginal data initiative: Survey component Archived
    Articles and reports: 11-522-X20040018655
    Description:

    The design of surveys for Aboriginal groups brings challenges: identification of the target population, challenges in survey design, remoteness and response burden.

    Release date: 2005-10-27
  • 3. Methodological challenges in a survey on the ethnic and cultural diversity of the Canadian population Archived
    Articles and reports: 11-522-X20040018734
    Geography: Canada
    Description:

    The Ethnic Diversity Survey generated methodological challenges like choosing the sampling plan, developing the questionnaire, collecting the data, weighting the data and estimating the variance.

    Release date: 2005-10-27
  • 4. Thoughts on the future of surveys Archived
    Articles and reports: 11-522-X20040018744
    Description:

    I will try to look at the future of survey research in the light of the incredible developments in information technology. I will speculate on what new technologies might contribute to doing surveys differently.

    Release date: 2005-10-27
  • 5. The challenge of collecting information on the involvement of aboriginal people in the Canadian criminal justice system Archived
    Articles and reports: 11-522-X20040018748
    Description:

    Given the small numbers of Aboriginal people, survey sample sizes are usually too small to permit sufficient analysis of these small groups. This paper discusses efforts that are being made by the Canadian Centre for Justice Statistics in this regard.

    Release date: 2005-10-27
  • 6. The effect of record linkage errors on risk estimates in cohort mortality studies Archived
    Articles and reports: 12-001-X20050018083
    Description:

    The advent of computerized record linkage methodology has facilitated the conduct of cohort mortality studies in which exposure data in one database are electronically linked with mortality data from another database. This, however, introduces linkage errors due to mismatching an individual from one database with a different individual from the other database. In this article, the impact of linkage errors on estimates of epidemiological indicators of risk such as standardized mortality ratios and relative risk regression model parameters is explored. It is shown that the observed and expected number of deaths are affected in opposite direction and, as a result, these indicators can be subject to bias and additional variability in the presence of linkage errors.

    Release date: 2005-07-21
  • 7. Using mean bootstrap weights in stata: A BSWREG revision Archived
    Articles and reports: 12-002-X20050018031
    Description:

    This article presents revisions to a Stata "bswreg" ado file that calculates variance estimates using bootstrap weights. This revision adds new output and analytic features. The main feature added to the program enables researchers to apply mean bootstrap weights while accounting for the number of weights used to generate the average bootstrap weight. The Workplace and Employee Survey dataset will be used to illustrate the usefulness of this program. This revised version of the "bswreg" command is still an easy to use flexible tool, which is compatible with a wide variety of regression analytical techniques and datasets. The bswreg command and design-based bootstrap weights should only be used for inference when it is theoretically valid.

    Release date: 2005-06-23
  • 8. An analysis of classification error for the revised Current Population Survey Employment questions Archived
    Articles and reports: 12-001-X20040027747
    Description:

    The reduced accuracy of the revised classification of unemployed persons in the Current Population Survey (CPS) was documented in Biemer and Bushery (2000). In this paper, we provide additional evidence of this anomaly and attempt to trace the source of the error through extended analysis of the CPS data before and after the redesign. The paper presents an novel approach decomposing the error in a complex classification process, such as the CPS labor force status classification, using Markov Latent Class Analysis (MLCA). To identify the cause of the apparent reduction in unemployed classification accuracy, we identify the key question components that determine the classifications and estimate the contribution of each of these question components to the total error in the classification process. This work provides guidance for further investigation into the root causes of the errors in the collection of labor force data in the CPS possibly through cognitive laboratory and/or field experiments.

    Release date: 2005-02-03
  • 9. Robust generalized regression estimation Archived
    Articles and reports: 12-001-X20040027752
    Description:

    The Best Linear Unbiased (BLU) estimator (or predictor) of a population total is based on the following two assumptions: i) the estimation model underlying the BLU estimator is correctly specified and ii) the sampling design is ignorable with respect to the estimation model. In this context, an estimator is robust if it stays close to the BLU estimator when both assumptions hold and if it keeps good properties when one or both assumptions are not fully satisfied. Robustness with respect to deviations from assumption (i) is called model robustness while robustness with respect to deviations from assumption (ii) is called design robustness. The Generalized Regression (GREG) estimator is often viewed as being robust since its property of being Asymptotically Design Unbiased (ADU) is not dependent on assumptions (i) and (ii). However, if both assumptions hold, the GREG estimator may be far less efficient than the BLU estimator and, in that sense, it is not robust. The relative inefficiency of the GREG estimator as compared to the BLU estimator is caused by widely dispersed design weights. To obtain a design-robust estimator, we thus propose a compromise between the GREG and the BLU estimators. This compromise also provides some protection against deviations from assumption (i). However, it does not offer any protection against outliers, which can be viewed as a consequence of a model misspecification. To deal with outliers, we use the weighted generalized M-estimation technique to reduce the influence of units with large weighted population residuals. We propose two practical ways of implementing M-estimators for multipurpose surveys; either the weights of influential units are modified and a calibration approach is used to obtain a single set of robust estimation weights or the values of influential units are modified. Some properties of the proposed approach are evaluated in a simulation study using a skewed finite population created from real survey data.

    Release date: 2005-02-03
  • 10. Dealing with movers in a longitudinal study of children Archived
    Articles and reports: 11-522-X20030017522
    Description:

    This paper describes the design and adjustment methods for handling movers in the U.S. Early Childhood Longitudinal Study, Kindergarten Class of 1998/99 (ECLS-K). The paper also discusses how subsampling movers and adjusting for mover non-response affect the survey goal of accurately characterizing the academic growth and experiences of children.

    Release date: 2005-01-26
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Articles and reports (19)

Articles and reports (19) (0 to 10 of 19 results)

  • 1. Surveying Aboriginal and Torres Strait islander peoples: Strategies and methodologies of the Australian Bureau of Statistics Archived
    Articles and reports: 11-522-X20040018654
    Description:

    In Australia, cultural considerations influence the statistical activity with regards to Indigenous population. The paper discusses survey designs, operations, estimation and dissemination.

    Release date: 2005-10-27
  • 2. Aboriginal data initiative: Survey component Archived
    Articles and reports: 11-522-X20040018655
    Description:

    The design of surveys for Aboriginal groups brings challenges: identification of the target population, challenges in survey design, remoteness and response burden.

    Release date: 2005-10-27
  • 3. Methodological challenges in a survey on the ethnic and cultural diversity of the Canadian population Archived
    Articles and reports: 11-522-X20040018734
    Geography: Canada
    Description:

    The Ethnic Diversity Survey generated methodological challenges like choosing the sampling plan, developing the questionnaire, collecting the data, weighting the data and estimating the variance.

    Release date: 2005-10-27
  • 4. Thoughts on the future of surveys Archived
    Articles and reports: 11-522-X20040018744
    Description:

    I will try to look at the future of survey research in the light of the incredible developments in information technology. I will speculate on what new technologies might contribute to doing surveys differently.

    Release date: 2005-10-27
  • 5. The challenge of collecting information on the involvement of aboriginal people in the Canadian criminal justice system Archived
    Articles and reports: 11-522-X20040018748
    Description:

    Given the small numbers of Aboriginal people, survey sample sizes are usually too small to permit sufficient analysis of these small groups. This paper discusses efforts that are being made by the Canadian Centre for Justice Statistics in this regard.

    Release date: 2005-10-27
  • 6. The effect of record linkage errors on risk estimates in cohort mortality studies Archived
    Articles and reports: 12-001-X20050018083
    Description:

    The advent of computerized record linkage methodology has facilitated the conduct of cohort mortality studies in which exposure data in one database are electronically linked with mortality data from another database. This, however, introduces linkage errors due to mismatching an individual from one database with a different individual from the other database. In this article, the impact of linkage errors on estimates of epidemiological indicators of risk such as standardized mortality ratios and relative risk regression model parameters is explored. It is shown that the observed and expected number of deaths are affected in opposite direction and, as a result, these indicators can be subject to bias and additional variability in the presence of linkage errors.

    Release date: 2005-07-21
  • 7. Using mean bootstrap weights in stata: A BSWREG revision Archived
    Articles and reports: 12-002-X20050018031
    Description:

    This article presents revisions to a Stata "bswreg" ado file that calculates variance estimates using bootstrap weights. This revision adds new output and analytic features. The main feature added to the program enables researchers to apply mean bootstrap weights while accounting for the number of weights used to generate the average bootstrap weight. The Workplace and Employee Survey dataset will be used to illustrate the usefulness of this program. This revised version of the "bswreg" command is still an easy to use flexible tool, which is compatible with a wide variety of regression analytical techniques and datasets. The bswreg command and design-based bootstrap weights should only be used for inference when it is theoretically valid.

    Release date: 2005-06-23
  • 8. An analysis of classification error for the revised Current Population Survey Employment questions Archived
    Articles and reports: 12-001-X20040027747
    Description:

    The reduced accuracy of the revised classification of unemployed persons in the Current Population Survey (CPS) was documented in Biemer and Bushery (2000). In this paper, we provide additional evidence of this anomaly and attempt to trace the source of the error through extended analysis of the CPS data before and after the redesign. The paper presents an novel approach decomposing the error in a complex classification process, such as the CPS labor force status classification, using Markov Latent Class Analysis (MLCA). To identify the cause of the apparent reduction in unemployed classification accuracy, we identify the key question components that determine the classifications and estimate the contribution of each of these question components to the total error in the classification process. This work provides guidance for further investigation into the root causes of the errors in the collection of labor force data in the CPS possibly through cognitive laboratory and/or field experiments.

    Release date: 2005-02-03
  • 9. Robust generalized regression estimation Archived
    Articles and reports: 12-001-X20040027752
    Description:

    The Best Linear Unbiased (BLU) estimator (or predictor) of a population total is based on the following two assumptions: i) the estimation model underlying the BLU estimator is correctly specified and ii) the sampling design is ignorable with respect to the estimation model. In this context, an estimator is robust if it stays close to the BLU estimator when both assumptions hold and if it keeps good properties when one or both assumptions are not fully satisfied. Robustness with respect to deviations from assumption (i) is called model robustness while robustness with respect to deviations from assumption (ii) is called design robustness. The Generalized Regression (GREG) estimator is often viewed as being robust since its property of being Asymptotically Design Unbiased (ADU) is not dependent on assumptions (i) and (ii). However, if both assumptions hold, the GREG estimator may be far less efficient than the BLU estimator and, in that sense, it is not robust. The relative inefficiency of the GREG estimator as compared to the BLU estimator is caused by widely dispersed design weights. To obtain a design-robust estimator, we thus propose a compromise between the GREG and the BLU estimators. This compromise also provides some protection against deviations from assumption (i). However, it does not offer any protection against outliers, which can be viewed as a consequence of a model misspecification. To deal with outliers, we use the weighted generalized M-estimation technique to reduce the influence of units with large weighted population residuals. We propose two practical ways of implementing M-estimators for multipurpose surveys; either the weights of influential units are modified and a calibration approach is used to obtain a single set of robust estimation weights or the values of influential units are modified. Some properties of the proposed approach are evaluated in a simulation study using a skewed finite population created from real survey data.

    Release date: 2005-02-03
  • 10. Dealing with movers in a longitudinal study of children Archived
    Articles and reports: 11-522-X20030017522
    Description:

    This paper describes the design and adjustment methods for handling movers in the U.S. Early Childhood Longitudinal Study, Kindergarten Class of 1998/99 (ECLS-K). The paper also discusses how subsampling movers and adjusting for mover non-response affect the survey goal of accurately characterizing the academic growth and experiences of children.

    Release date: 2005-01-26
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