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

Two-level proportional hazards models.

Jerry J Maples1, Susan A Murphy, William G Axinn

  • 1The Methodology Center and Department of Statistics, Pennsylvania State University, 326 Thomas Building, University Park, Pennsylvania 16802, USA. maples@stat.psu.edu

Biometrics
|December 24, 2002
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

Is More Always Better With Digital Health Interventions? Shifting Engagement From Maximizing Use to Supporting Health.

Mayo Clinic proceedings. Digital health·2026
Same author

Effective monitoring of online AI decision-making algorithms in just-in-time adaptive interventions.

NPJ digital medicine·2026
Same author

SigmaScheduling: Uncertainty-Informed Scheduling of Decision Points for Intelligent Mobile Health Interventions.

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks·2026
Same author

Non-Stationary Latent Auto-Regressive Bandits.

Reinforcement learning journal·2026
Same author

Harnessing Causality in Reinforcement Learning With Bagged Decision Times.

Proceedings of machine learning research·2026
Same author

Digital Twins for Just-in-Time Adaptive Interventions (JITAIs): Framework for Optimizing and Continually Improving JITAIs.

Journal of medical Internet research·2026
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 introduces a new two-level proportional hazards model to analyze factors influencing contraceptive use. The model accurately estimates effects of education and child education access on permanent contraceptive adoption.

Area of Science:

  • Biostatistics
  • Demography
  • Epidemiology

Background:

  • Understanding determinants of contraceptive use is crucial for family planning and public health initiatives.
  • Previous models may not fully capture the hierarchical nature of individual decisions within group contexts.

Purpose of the Study:

  • To extend the proportional hazards model into a two-level framework incorporating random intercepts and coefficients.
  • To investigate the influence of education and children's access to education on permanent contraceptive use among Nepalese women.

Main Methods:

  • Development and application of a two-level proportional hazards model.
  • Estimation of multilevel model parameters using a combination of Expectation-Maximization (EM) and Newton-Raphson algorithms.
  • Assessment of standard error estimation using observed information and profile likelihood information methods.

Related Experiment Videos

Main Results:

  • The proposed method yields approximately unbiased and normally distributed estimators for fixed effects coefficients, even with small sample sizes (e.g., 50 groups).
  • The two-level hazard model effectively examines the relationship between education, child education access, and the initiation of permanent contraceptive use.

Conclusions:

  • The developed two-level proportional hazards model provides a robust statistical framework for analyzing complex health behaviors.
  • Education and children's access to education are identified as significant factors associated with permanent contraceptive adoption in the studied population.