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Multipopulation survey designs: five types with seven shared aspects.

L Kish

    International Statistical Review = Revue Internationale De Statistique
    |August 1, 1994
    PubMed
    Summary
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    This study defines five types of multipopulation surveys, emphasizing deliberate design over ad hoc use. Standardization is crucial for unbiased comparisons, while flexible sampling reduces costs and variance.

    Area of Science:

    • Social Sciences
    • Survey Methodology
    • Comparative Research

    Background:

    • Multipopulation surveys are increasingly used for comparative research.
    • Existing literature often lacks clear distinctions between different survey designs.
    • The need for rigorous methodological frameworks in multipopulation studies is evident.

    Purpose of the Study:

    • To define and describe five distinct types of multipopulation survey designs.
    • To emphasize the importance of deliberate, planned survey methodologies.
    • To highlight critical aspects for ensuring valid cross-survey comparisons.

    Main Methods:

    • Classification of five multipopulation survey types: periodic, multidomain, multinational, cumulated/combined samples, and controlled observations/quasi-experimental designs.
    Keywords:
    Comparative StudiesResearch MethodologySampling StudiesStudiesSurvey MethodologySurveysWorld

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  • Emphasis on deliberate design principles rather than post hoc data utilization.
  • Identification of key aspects requiring standardization for comparative validity.
  • Main Results:

    • Five distinct multipopulation survey designs are clearly delineated.
    • A critical distinction is made between seven key survey aspects.
    • Standardization of definitions, methods, and measurements is identified as essential for unbiased comparisons.
    • Flexibility in sampling design and size is permissible and beneficial for reducing variance and costs.

    Conclusions:

    • Deliberate and standardized design is paramount for valid multipopulation survey research.
    • Careful consideration of survey aspects ensures comparability across different populations.
    • Optimizing sampling strategies can enhance efficiency without compromising validity.