Optimal designs for full and partial likelihood information -- with application to survival models

DOI10.1016/J.JSPI.2015.03.007zbMath1326.62170OpenAlexW1975638297MaRDI QIDQ894783

Alan C. Kimber, Maria Konstantinou, Stefanie Biedermann

Publication date: 23 November 2015

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: http://oro.open.ac.uk/72262/1/PDF_72262.pdf

zbMATH Keywords

partial likelihoodoptimal designright-censoringCox's modelfull likelihood

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Nonparametric estimation (62G05) Censored data models (62N01) Reliability and life testing (62N05)

Related Items (4)

Information measures and design issues in the study of mortality deceleration: findings for the gamma-Gompertz model ⋮ Optimal experimental designs for accelerated failure time with Type I and random censoring ⋮ Model robust designs for survival trials ⋮ Optimal design of experiments with the observation censoring driven by random enrollment of subjects

Cites Work

• Cox's regression model for counting processes: A large sample study
• Investigating design for survival models
• Optimal experimental designs for partial likelihood information
• Efficiency of Balanced Treatment Allocation for Survival Analysis
• OPTIMAL DESIGNS FOR FITTING A PROPORTIONAL HAZARDS REGRESSION MODEL TO DATA SUBJECT TO CENSORING
• The Efficiency of Cox's Likelihood Function for Censored Data
• Planning step‐stress life test with progressively type I group‐censored exponential data
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