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Survival models for fertility evaluation.

K E Boyle, T B Starr

    Journal of the American Statistical Association
    |December 1, 1985
    PubMed
    Summary
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    This study introduces two proportional hazards models to evaluate cohort fertility, incorporating time-dependent covariates. Both models yielded similar results for exposure effects in a hazardous workplace study.

    Area of Science:

    • Epidemiology
    • Biostatistics
    • Demography

    Background:

    • Fertility evaluation requires sophisticated statistical models to account for individual heterogeneity.
    • Time-dependent covariates are crucial for capturing dynamic factors influencing fertility outcomes.

    Purpose of the Study:

    • To develop and compare two proportional hazards models for cohort fertility analysis.
    • To assess the impact of hazardous workplace exposure on fertility using these models.

    Main Methods:

    • Construction of two proportional hazards models incorporating time-dependent covariates.
    • Model 1: Utilizes U.S. birth rates stratified by maternal age, race, parity, and birth cohort as underlying hazards.
    • Model 2: Employs Cox regression with stratified underlying hazards as nuisance parameters.
    Keywords:
    AmericasCohort AnalysisDemographic FactorsDeveloped CountriesDeveloping CountriesEstimation TechnicsEthnic GroupsFertilityFertility MeasurementsHeterogeneityMaternal AgeMathematical ModelModels, TheoreticalNorth AmericaNorthern AmericaParityPopulationPopulation CharacteristicsPopulation DynamicsResearch MethodologyUnited States

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    Main Results:

    • Both models effectively estimate covariate effects on fertility.
    • Application to wives of potentially hazardous exposed workers showed practically equivalent point estimates and standard errors for exposure effects.
    • Model 1 required adjustments for maternal age and nulliparity.

    Conclusions:

    • Proportional hazards models with time-dependent covariates offer robust methods for fertility evaluation.
    • The two proposed models provide comparable results for estimating exposure effects, offering flexibility in analysis.
    • These models are valuable tools for epidemiological studies investigating fertility and environmental exposures.