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All (5) ((5 results))

  • 1. Maximum likelihood estimation from complex sample surveys Archived
    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
  • 2. Robust model-based methods for analytic surveys Archived
    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
  • 3. Bibliography on capture-recapture modelling with application to census undercount adjustment Archived
    Articles and reports: 12-001-X199200114494
    Description:

    This article presents a selected annotated bibliography of the literature on capture-recapture (dual system) estimation of population size, on extensions to the basic methodology, and the application of these techniques in the context of census undercount estimation.

    Release date: 1992-06-15
  • 4. Restricted maximum likelihood (REML) estimation in empirical Bayes smoothing of census undercount Archived
    Articles and reports: 12-001-X199200114498
    Description:

    One way to assess the undercount at subnational levels (e.g. the state level) is to obtain sample data from a post-enumeration survey, and then smooth those data based on a linear model of explanatory variables. The relative importance of sampling-error variances to corresponding model-error variances determines the amount of smoothing. Maximum likelihood estimation can lead to oversmoothing, so making the assessment of undercount over-reliant on the linear model. Restricted maximum likelihood (REML) estimators do not suffer from this drawback. Empirical Bayes prediction of undercount based on REML will be presented in this article, and will be compared to maximum likelihood and a method of moments by both simulation and example. Large-sample distributional properties of the REML estimators allow accurate mean squared prediction errors of the REML-based smoothers to be computed.

    Release date: 1992-06-15
  • 5. Should we have adjusted the U.S. census of 1980? Archived
    Articles and reports: 12-001-X199200114499
    Description:

    This paper reviews some of the arguments for and against adjusting the U.S. census of 1980, and the decision of the court.

    Release date: 1992-06-15
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Analysis (5)

Analysis (5) ((5 results))

  • 1. Maximum likelihood estimation from complex sample surveys Archived
    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
  • 2. Robust model-based methods for analytic surveys Archived
    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
  • 3. Bibliography on capture-recapture modelling with application to census undercount adjustment Archived
    Articles and reports: 12-001-X199200114494
    Description:

    This article presents a selected annotated bibliography of the literature on capture-recapture (dual system) estimation of population size, on extensions to the basic methodology, and the application of these techniques in the context of census undercount estimation.

    Release date: 1992-06-15
  • 4. Restricted maximum likelihood (REML) estimation in empirical Bayes smoothing of census undercount Archived
    Articles and reports: 12-001-X199200114498
    Description:

    One way to assess the undercount at subnational levels (e.g. the state level) is to obtain sample data from a post-enumeration survey, and then smooth those data based on a linear model of explanatory variables. The relative importance of sampling-error variances to corresponding model-error variances determines the amount of smoothing. Maximum likelihood estimation can lead to oversmoothing, so making the assessment of undercount over-reliant on the linear model. Restricted maximum likelihood (REML) estimators do not suffer from this drawback. Empirical Bayes prediction of undercount based on REML will be presented in this article, and will be compared to maximum likelihood and a method of moments by both simulation and example. Large-sample distributional properties of the REML estimators allow accurate mean squared prediction errors of the REML-based smoothers to be computed.

    Release date: 1992-06-15
  • 5. Should we have adjusted the U.S. census of 1980? Archived
    Articles and reports: 12-001-X199200114499
    Description:

    This paper reviews some of the arguments for and against adjusting the U.S. census of 1980, and the decision of the court.

    Release date: 1992-06-15
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