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Estimating menarcheal age distribution from partially recalled data.

Sedigheh Mirzaei Salehabadi1, Debasis Sengupta2, Rahul Ghosal3

  • 1St. Jude Children's Research Hospital, Memphis, USA.

Biostatistics (Oxford, England)
|May 16, 2019
PubMed
Summary
This summary is machine-generated.

Estimating the age of menarche (first menstrual period) is challenging due to memory recall issues. This study developed statistical models to accurately estimate menarcheal age distributions from incomplete data.

Keywords:
Current status dataInformative censoringInterval censoringMaximum likelihood estimationRetrospective studySelf-consistency

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Area of Science:

  • Biostatistics
  • Reproductive Health
  • Epidemiology

Background:

  • Accurate estimation of menarcheal age distribution is crucial for understanding female reproductive development.
  • Recall of the exact date of menarche can be difficult for adolescent and young adult females, leading to interval-censored data.

Purpose of the Study:

  • To develop and evaluate statistical methods for estimating the age distribution of menarche from interval-censored recall data.
  • To account for informative censoring caused by memory fading and the interplay between age and calendar time.

Main Methods:

  • Proposed a statistical model where recall probabilities depend on time since menarche, using multinomial regression for parametric estimation.
  • Developed a non-parametric maximum likelihood estimator and a computationally simpler approximation.
  • Utilized Monte Carlo simulations to assess the performance of parametric and non-parametric estimators.

Main Results:

  • Established consistency and asymptotic normality for the parametric maximum likelihood estimator.
  • Demonstrated consistency for both parametric and non-parametric estimators under mild conditions.
  • Showed that incorporating partially recalled data significantly reduces confidence intervals for the survival function.

Conclusions:

  • Statistical modeling can effectively address challenges posed by interval-censored recall data in estimating menarcheal age.
  • The proposed methods provide more precise estimates of the menarcheal age distribution by utilizing all available data.
  • The findings have implications for epidemiological studies on female reproductive health and development.