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All (3) ((3 results))

  • 1. Evaluating the reasonableness of data: using cross ratios and chi-square measures Archived
    Articles and reports: 11-522-X20010016236
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The Uniform Crime Reporting (UCR) Program has devoted a considerable amount of resources in a continuous effort to improve the quality of its data. In this paper, the authors introduce and discuss the use of the cross-ratios and chi-square measures to evaluate the rationality of the data. The UCR data is used to empirically illustrate this approach.

    Release date: 2002-09-12
  • 2. Coordinating samples using the microstrata methodology Archived
    Articles and reports: 11-522-X20010016252
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The use of sample co-ordination in business surveys is crucial because it provides a way of smoothing out the survey burden. In many co-ordination methodologies, the random numbers representing the units are permanent and the sample selection method varies. In the microstrata methodology, however, it is the selection function that is permanent. On the other hand, random numbers are systematically rearranged between units for different co-ordination purposes: smoothing out the burden, updating panels or minimizing the overlap between two surveys. These rearrangements are made in the intersections of strata, known as microstrata. This microstrata method has good, mathematical properties and demonstrates a general approach to sample co-ordination in which births, deaths and strata changes are automatically handled. There are no particular constraints on stratification and rotation rates of panels. Two software programs have been written to implement this method and its evolutions: SALOMON in 1998, and MICROSTRAT in 2001.

    Release date: 2002-09-12
  • 3. Optimization techniques for edit validation and data imputation Archived
    Articles and reports: 11-522-X20010016306
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The paper deals with concerns regarding the problem of automatic detection and correction of inconsistent or out-of-range data in a general process of statistical data collection. The proposed approach is capable of handling both qualitative and quantitative values. The purpose of this new approach is to overcome the computational limits of the Fellegi-Holt method, while maintaining its positive features. As customary, data records must respect a set of rules in order to be declared correct. By encoding the rules with linear inequalities, we develop mathematical models for the problems of interest. As a first relevant point, by solving a sequence of feasibility problems, the set of rules itself is checked for inconsistency or redundancy. As a second relevant point, imputation is performed by solving a sequence of set-covering problems.

    Release date: 2002-09-12
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  • 1. Evaluating the reasonableness of data: using cross ratios and chi-square measures Archived
    Articles and reports: 11-522-X20010016236
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The Uniform Crime Reporting (UCR) Program has devoted a considerable amount of resources in a continuous effort to improve the quality of its data. In this paper, the authors introduce and discuss the use of the cross-ratios and chi-square measures to evaluate the rationality of the data. The UCR data is used to empirically illustrate this approach.

    Release date: 2002-09-12
  • 2. Coordinating samples using the microstrata methodology Archived
    Articles and reports: 11-522-X20010016252
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The use of sample co-ordination in business surveys is crucial because it provides a way of smoothing out the survey burden. In many co-ordination methodologies, the random numbers representing the units are permanent and the sample selection method varies. In the microstrata methodology, however, it is the selection function that is permanent. On the other hand, random numbers are systematically rearranged between units for different co-ordination purposes: smoothing out the burden, updating panels or minimizing the overlap between two surveys. These rearrangements are made in the intersections of strata, known as microstrata. This microstrata method has good, mathematical properties and demonstrates a general approach to sample co-ordination in which births, deaths and strata changes are automatically handled. There are no particular constraints on stratification and rotation rates of panels. Two software programs have been written to implement this method and its evolutions: SALOMON in 1998, and MICROSTRAT in 2001.

    Release date: 2002-09-12
  • 3. Optimization techniques for edit validation and data imputation Archived
    Articles and reports: 11-522-X20010016306
    Description:

    This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.

    The paper deals with concerns regarding the problem of automatic detection and correction of inconsistent or out-of-range data in a general process of statistical data collection. The proposed approach is capable of handling both qualitative and quantitative values. The purpose of this new approach is to overcome the computational limits of the Fellegi-Holt method, while maintaining its positive features. As customary, data records must respect a set of rules in order to be declared correct. By encoding the rules with linear inequalities, we develop mathematical models for the problems of interest. As a first relevant point, by solving a sequence of feasibility problems, the set of rules itself is checked for inconsistency or redundancy. As a second relevant point, imputation is performed by solving a sequence of set-covering problems.

    Release date: 2002-09-12
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