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Related Experiment Videos

Moving in a given year: a study in research design and data analysis.

R B Ginsberg

    Tijdschrift Voor Economische En Sociale Geografie = Journal of Economic and Social Geography = Revue De Geographie Economique Et Humaine = Zeitschrift Fur Okonomische Und Soziale Geographie = Revista De Geografia Economica Y Social
    |January 1, 1983
    PubMed
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    Timing and duration effects in residence histories and other longitudinal data: I. Stochastic and statistical models.

    Regional science and urban economics·1979
    Same author

    Timing and duration effects in residence histories and other longitudinal data: Part 1. Stochastic and statistical models; Part 2. Studies of duration effects in Norway, 1965-1971.

    Regional science and urban economics·1979
    Same author

    Timing and duration effects in residence histories and other longitudinal data: II. Studies of duration effects in Norway, 1965-1971.

    Regional science and urban economics·1979
    Same author

    Tests of stochastic models of timing in mobility histories: comparison of information derived from different observation plans.

    Environment & planning A·1979
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    The relationship between timing of moves and choice of destination in stochastic models of migration.

    Environment & planning A·1978
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    The effect of lactation on the length of the post partum anovulatory period: an application of a bivariate stochastic model.

    Theoretical population biology·1973

    This study examines residential mobility by analyzing residence history data. It finds that cross-sectional survey data is often sufficient for understanding the probability of moving, simplifying mobility research.

    Area of Science:

    • Demography
    • Sociology
    • Spatial Statistics

    Background:

    • Understanding residential mobility patterns is crucial for urban planning and social science research.
    • Complete residence histories offer detailed insights but are data-intensive.

    Purpose of the Study:

    • To analyze the distribution of times between residential moves.
    • To evaluate the relationship between duration of residence and the probability of moving.
    • To assess the feasibility of using cross-sectional data for mobility studies.

    Main Methods:

    • Utilized complete residence histories from the Norwegian Population Register (1965-1971).
    • Generated 'ideal' and point-in-time residence duration datasets.
    • Employed stochastic models to analyze mobility histories and probability of moving.
    Keywords:
    Data AnalysisDemographic FactorsDeveloped CountriesEuropeGeographic FactorsMigrationMigration, InternalModels, TheoreticalNorthern EuropeNorwayPopulationPopulation DynamicsProbabilityResearch MethodologyResidence CharacteristicsScandinaviaSpatial DistributionStatistical StudiesStudiesStudy DesignTime Factors

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    Main Results:

    • Demonstrated that cross-sectional survey data is sufficient for many analyses of mobility probability.
    • Highlighted the relationship between residence duration and the likelihood of moving.
    • Identified methodological challenges with sparse tabular data in socio-demographic studies.

    Conclusions:

    • Cross-sectional data can effectively substitute for complete residence histories in many mobility research contexts.
    • Methodological considerations are important when using aggregated data for detailed projections.
    • The study contributes to efficient data utilization in demographic research.