Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Fitting time-dependent multicompartment models: a case study.

M J Faddy1, M C Jones

  • 1Department of Statistics, University of Birmingham, United Kingdom.

Biometrics
|June 1, 1988
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Erratum: "Radiation, optical, power flow, and electrical diagnostics at the Z facility: Layout and techniques utilized to operate in the harsh environment" [Rev. Sci. Instrum. 94, 031102 (2023)].

The Review of scientific instruments·2024
Same author

Time-of-flight vs time-of-arrival in neutron spectroscopic measurements for high energy density plasmas.

The Review of scientific instruments·2024
Same author

Soft x-ray power diagnostics for fusion experiments at NIF, Omega, and Z facilities.

The Review of scientific instruments·2023
Same author

Radiation, optical, power flow, and electrical diagnostics at the Z facility: Layout and techniques utilized to operate in the harsh environment.

The Review of scientific instruments·2023
Same author

Neutron time-of-flight detectors (nTOF) used at Sandia's Z-Machine.

The Review of scientific instruments·2022
Same author

On the 'optimal' density power divergence tuning parameter.

Journal of applied statistics·2022
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
Same journal

Discussion on "INTACT: a method for integration of longitudinal physical activity data from multiple sources" by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou.

Biometrics·2026
See all related articles

This study models ovarian follicle dynamics in mice using a novel multicompartment approach. Combining parametric and nonparametric methods improved model accuracy for tracking follicle development.

Area of Science:

  • Reproductive biology
  • Mathematical modeling
  • Biostatistics

Background:

  • Ovarian follicle dynamics are crucial for reproductive success.
  • Accurate modeling of these dynamics aids in understanding fertility and developing interventions.
  • Existing models may lack the precision to capture complex, time-dependent changes.

Purpose of the Study:

  • To develop and refine a multicompartment model for ovarian follicle dynamics in mice.
  • To integrate parametric and nonparametric approaches for improved curve fitting.
  • To enhance the biological realism and predictive power of ovarian dynamics models.

Main Methods:

  • Fitted a multicompartment model with time-dependent transfer rates to mouse ovarian follicle data.
  • Employed nonparametric regression (spline smoothers) to guide parametric model refinement.

Related Experiment Videos

  • Investigated the use of three-stage step functions for compartmental transition rates.

    • Main Results:

    • The interplay between parametric and nonparametric methods yielded a refined model.
    • Nonparametric estimates informed the structure of the parametric model.
    • Three-stage step functions for transition rates closely mimicked nonparametric regression estimates.

    Conclusions:

    • A hybrid modeling approach combining parametric and nonparametric methods enhances the accuracy of ovarian follicle dynamics models.
    • The refined model provides a more precise representation of follicular development.
    • This approach offers a robust framework for studying reproductive processes.