AbstractIn this paper, we propose a method to analyze survival data from a clinical trial that utilizes a dynamic randomization for subject enrollment. The method directly accounts for dynamic subject randomization process using a marked point process (MPP). Its corresponding martingale process is used to formulate an equation for estimating the treatment effect size and for hypothesis testing. We perform simulation analyses to evaluate the outcomes of the proposed method as well as the conventional log rank method and re-randomized testing procedure
Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing...
Indiana University-Purdue University Indianapolis (IUPUI)In medical research, data analysis often re...
An adaptive treatment strategy (ATS) is an outcome-guided algorithm that allows personalized treatme...
AbstractIn this paper, we propose a method to analyze survival data from a clinical trial that utili...
Treatment of complex diseases such as cancer, HIV, leukemia and depression usually follows complex t...
Adaptive treatment strategies are comprehensive methods for treating chronic diseases according to p...
Adaptive treatment strategies closely mimic the reality of a physician's prescription process where ...
Part I of this report appeared in the previous issue (Br. J. Cancer (1976) 34,585), and discussed th...
Abstract Background Ideally clinical trials should use some form of randomization for allocating par...
Sequentially randomized designs are becoming common in biomedical research, particularlyin clinical ...
In oncology, toxicity is typically observable shortly after a chemotherapy treatment, whereas effica...
In this paper, we discuss a response adaptive randomization method, and why it should be used in cli...
Randomised controlled trials are considered the gold standard study design, as random treatment assi...
The random allocation of patients to treatments is a crucial step in the design and conduct of a ran...
Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing...
Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing...
Indiana University-Purdue University Indianapolis (IUPUI)In medical research, data analysis often re...
An adaptive treatment strategy (ATS) is an outcome-guided algorithm that allows personalized treatme...
AbstractIn this paper, we propose a method to analyze survival data from a clinical trial that utili...
Treatment of complex diseases such as cancer, HIV, leukemia and depression usually follows complex t...
Adaptive treatment strategies are comprehensive methods for treating chronic diseases according to p...
Adaptive treatment strategies closely mimic the reality of a physician's prescription process where ...
Part I of this report appeared in the previous issue (Br. J. Cancer (1976) 34,585), and discussed th...
Abstract Background Ideally clinical trials should use some form of randomization for allocating par...
Sequentially randomized designs are becoming common in biomedical research, particularlyin clinical ...
In oncology, toxicity is typically observable shortly after a chemotherapy treatment, whereas effica...
In this paper, we discuss a response adaptive randomization method, and why it should be used in cli...
Randomised controlled trials are considered the gold standard study design, as random treatment assi...
The random allocation of patients to treatments is a crucial step in the design and conduct of a ran...
Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing...
Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing...
Indiana University-Purdue University Indianapolis (IUPUI)In medical research, data analysis often re...
An adaptive treatment strategy (ATS) is an outcome-guided algorithm that allows personalized treatme...