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The multistate life table with duration-dependence.

D A Wolf

    Mathematical Population Studies
    |January 1, 1988
    PubMed
    Summary
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    This study proposes a new life table method accounting for age and duration of risk. It enables new cohort history indices, demonstrated with a marital status model and Finnish data.

    Area of Science:

    • Demography
    • Sociology
    • Gerontology

    Background:

    • Traditional life tables often assume risk rates depend solely on age.
    • This limitation overlooks critical factors like duration of exposure, particularly in dynamic life events such as marital status changes.

    Purpose of the Study:

    • To generalize multistate life tables to incorporate risk rates dependent on both age and duration of exposure.
    • To introduce novel summary indices for life-table cohort histories, including mean and median time in specific states.

    Main Methods:

    • The proposed method utilizes a linear integration hypothesis for approximation.
    • It extends increment-decrement life table methodologies.
    • Applies the method to a four-state marital status model.
    Keywords:
    Age FactorsCohort AnalysisData AnalysisDemographic AnalysisDemographic FactorsDeveloped CountriesDivorceEuropeEvaluationFinlandLife Table MethodLife TablesLinear RegressionMarital StatusMarkov ChainMarriageMarriage DurationMethodological StudiesModels, TheoreticalMultivariate AnalysisNorthern EuropeNuptialityPopulationPopulation CharacteristicsPopulation DynamicsProbabilityResearch MethodologyScandinaviaStatistical RegressionStatistical StudiesStudiesTime FactorsWidowed

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    Main Results:

    • Demonstrates the derivation of new summary indices, such as mean and median duration in a status.
    • Illustrates how divorce and widowhood rates can vary by both marriage duration and age.
    • Provides an empirical example using 1984 Finnish period data for women aged 15-50.

    Conclusions:

    • The generalized life table method offers a more nuanced understanding of demographic processes.
    • It allows for the analysis of state transitions influenced by both age and duration.
    • The derived indices provide valuable insights into cohort experiences over time.