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A modification of a continuous time model for first conception.

S N Singh, K C Chakrabarty, V K Singh

    Demography
    |February 1, 1976
    PubMed
    Summary
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    This study introduces a new probability model for first conception times, improving fertility analysis by accounting for premarital conceptions. The model accurately describes data where females may already be pregnant at marriage.

    Area of Science:

    • Demography
    • Biostatistics
    • Reproductive Health

    Background:

    • The interval between marriage and first conception is crucial for fertility analysis.
    • Existing probability models often assume conception susceptibility at marriage, limiting their applicability.
    • Premarital conceptions can violate assumptions of standard fertility models.

    Purpose of the Study:

    • To present an inflated probability distribution model for first conception times.
    • To address limitations of existing models when premarital conceptions occur.
    • To provide a more accurate method for analyzing fertility data in specific populations.

    Main Methods:

    • Developed an inflated probability distribution based on Singh's continuous model.
    • Derived simple expressions for maximum likelihood estimators of model parameters.

    Related Experiment Videos

  • Outlined a method for calculating the asymptotic covariance matrix of estimators.

    • Main Results:

    • The proposed model effectively describes data on first conception times, particularly with premarital conceptions.
    • Maximum likelihood estimators for model parameters were obtained.
    • The model was successfully applied to four distinct datasets.

    Conclusions:

    • The new probability model enhances the analysis of fertility components by incorporating premarital conceptions.
    • The model offers a suitable alternative for fertility studies where females may conceive before marriage.
    • The derived estimators and covariance matrix provide a robust statistical framework for model application.