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Related Experiment Videos

Interval-censored event history analysis.

D Courgeau, J Najim

    Population. English Selection
    |January 1, 1996
    PubMed
    Summary
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    Event history analysis uses surveys or administrative data. Researchers compared these methods, finding administrative data limitations for tracking job or residential changes, impacting life course analysis accuracy.

    Area of Science:

    • Sociology
    • Demography
    • Historical Research

    Background:

    • Event history analysis is crucial for understanding life course trajectories.
    • Two primary data collection methods exist: retrospective surveys and administrative records.
    • Administrative data, while comprehensive, may lack crucial event details like job or residential changes.

    Purpose of the Study:

    • To assess the validity of event history analysis using incomplete administrative data.
    • To compare the accuracy of administrative data against dedicated survey data for life course events.

    Main Methods:

    • Utilized administrative data sources (vital registration, census, residence notifications).
    • Conducted an ad hoc survey to collect retrospective life course, family, and occupational histories.
    Keywords:
    Data CollectionDemographic AnalysisDeveloped CountriesEuropeEvent History AnalysisFranceMeasurementMediterranean CountriesMethodological StudiesResearch MethodologySampling StudiesStudiesSurveysValidityWestern Europe

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  • Performed comparative analysis between the two data sources.
  • Main Results:

    • Administrative data in France does not record job changes or residential moves.
    • The study validates the utility of administrative data despite its inherent limitations.
    • Comparative analysis revealed discrepancies due to missing event information.

    Conclusions:

    • Administrative data offers a valuable, albeit incomplete, resource for event history analysis.
    • Survey data remains essential for capturing events not registered in administrative systems.
    • Future research should explore methods to integrate or compensate for missing administrative data.