Random norming AIDS analysis of non-linear regression models with sequential informative dose selection

DOI10.1016/j.jspi.2019.09.003zbMath1436.62589arXiv1905.09722OpenAlexW2973314857WikidataQ127252701 ScholiaQ127252701MaRDI QIDQ2301071

Nancy Flournoy, William F. Rosenberger, Zhantao Lin

Publication date: 28 February 2020

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

Full work available at URL: https://arxiv.org/abs/1905.09722

zbMATH Keywords

stable convergenceinference for stochastic processesadaptive optimal designsgeneralized Cramér-Slutsky theoremrandom information measures

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) General nonlinear regression (62J02) Sequential statistical design (62L05)

Related Items

The effects of adaptation on maximum likelihood inference for nonlinear models with normal errors ⋮ Inference for a two-stage enrichment design ⋮ Efficiency of observed information adaptive designs in linear models

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Information in a two-stage adaptive optimal design
• Two-stage adaptive optimal design with fixed first-stage sample size
• Asymptotics in response-adaptive designs generated by a two-color, randomly reinforced urn
• On mixing and stability of limit theorems
• Asymptotic properties of maximum likelihood estimators with sample size recalculation
• Adaptive designs for selecting drug combinations based on efficacy-toxicity response
• Adaptive designs for dose-finding based on efficacy-toxicity response
• Optimal adaptive two-stage designs for phase II cancer clinical trials
• Bayesian Enrichment Strategies for Randomized Discontinuation Trials
• Bayesian Optimal Designs for Phase I Clinical Trials
• Optimizing randomized trial designs to distinguish which subpopulations benefit from treatment
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• Bias reduction of maximum likelihood estimates
• A Review of Some Aspects of Asymptotic Likelihood Theory for Stochastic Processes
• Stable Convergence and Stable Limit Theorems
• A Two-Sample Test for a Linear Hypothesis Whose Power is Independent of the Variance
• Conditional Estimation in Two-Stage Adaptive Designs